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values |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;2;3;4
| null | null | null |
Explainability;Interpretability;Counterfactuals;Algorithmic Recourse;Black-box Models;Machine Learning;Accountability;Consumer Protection;Adverse Action Notices
| null | 2.75 | null | null |
iclr
| -0.777778 | 0.96225 | null |
main
| 4.25 |
3;3;5;6
|
2;2;3;3
| null |
Low-Cost Algorithmic Recourse for Users With Uncertain Cost Functions
| null | null | 2.5 | 2.75 |
Reject
|
3;3;3;2
|
3;2;2;4
|
null | null |
2022
| 1.5 | null | null | 0 | null | null | null |
1;2;1;2
| null | null | null |
Hyper-parameter Optimization
| null | 1.75 | null | null |
iclr
| -0.852803 | -0.426401 | null |
main
| 3 |
1;3;3;5
|
3;3;1;2
| null |
Differentiable Hyper-parameter Optimization
| null | null | 2.25 | 4.25 |
Reject
|
5;4;5;3
|
1;2;2;2
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
2;2;4
| null | null | null | null | null | 2.666667 | null | null |
iclr
| 0 | -0.114708 | null |
main
| 5.333333 |
3;5;8
|
3;4;3
| null |
MA-CLIP: Towards Modality-Agnostic Contrastive Language-Image Pre-training
| null | null | 3.333333 | 4 |
Withdraw
|
4;4;4
|
2;2;4
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
1;2;2;3
| null | null | null |
deep learning;gradient descent;implicit bias;implicit regularization;Hessian;sharpness
| null | 2.25 | null | null |
iclr
| 0 | 0.301511 | null |
main
| 4 |
3;3;5;5
|
2;3;4;2
| null |
Implicit Jacobian regularization weighted with impurity of probability output
| null | null | 2.75 | 4 |
Reject
|
4;4;5;3
|
2;2;2;3
|
null |
University Children’s Hospital Basel; Politecnico di Milano; CADS, Human Technopole; St. Gallen Cantonal Hospital; University of Zürich; ETH Zürich; University Hospital Basel
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6333; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Laura Manduchi, Ričards Marcinkevičs, Michela Massi, Thomas Weikert, Alexander Sauter, Verena Gotta, Timothy Müller, Flavio Vasella, Marian Neidert, Marc Pfister, Bram Stieltjes, Julia E Vogt
|
https://iclr.cc/virtual/2022/poster/6333
|
survival analysis;clustering;healthcare;variational autoencoders;deep generative models
| null | 3.5 | null |
https://openreview.net/forum?id=RQ428ZptQfU
|
iclr
| -0.522233 | 1 | null |
main
| 7.5 |
6;8;8;8
|
3;4;4;4
|
https://iclr.cc/virtual/2022/poster/6333
|
A Deep Variational Approach to Clustering Survival Data
| null | null | 3.75 | 3.25 |
Poster
|
4;3;4;2
|
3;4;4;3
|
null | null |
2022
| 2.2 | null | null | 0 | null | null | null |
2;2;2;3;2
| null | null | null |
deep learning;regularization;overfitting;learning theory;neural network
| null | 2.2 | null | null |
iclr
| 0.166667 | 0 | null |
main
| 4.2 |
3;3;5;5;5
|
3;3;3;3;3
| null |
Improving Neural Network Generalization via Promoting Within-Layer Diversity
| null | null | 3 | 3.6 |
Reject
|
4;3;3;4;4
|
2;2;2;3;2
|
null |
Google; Microsoft Research, New York, NY
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6733; None
| null | 0 | null | null | null |
3;3;2;3
| null |
Yonathan Efroni, Dipendra Kumar Misra, Akshay Krishnamurthy, Alekh Agarwal, John Langford
|
https://iclr.cc/virtual/2022/poster/6733
|
Reinforcement Learning Theory;Invariant Representation;Rich Observation Reinforcement Learning;Exogenous Noise;Inverse Dynamics
| null | 2.75 | null |
https://openreview.net/forum?id=RQLLzMCefQu
|
iclr
| 0 | 0 | null |
main
| 8 |
8;8;8;8
|
4;4;3;4
|
https://iclr.cc/virtual/2022/poster/6733
|
Provably Filtering Exogenous Distractors using Multistep Inverse Dynamics
| null | null | 3.75 | 3.25 |
Oral
|
5;3;3;2
|
3;3;3;2
|
null |
Lunit; KakaoBrain
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/7017; None
| null | 0 | null | null | null |
2;3;4;3
| null |
Byungseok Roh, JaeWoong Shin, Wuhyun Shin, Saehoon Kim
|
https://iclr.cc/virtual/2022/poster/7017
|
Transformer Query Sparsification Mechanism;Efficient End-to-End Object Detection
| null | 3 | null |
https://openreview.net/forum?id=RRGVCN8kjim
|
iclr
| 0 | 0.555556 | null |
main
| 6.75 |
5;6;8;8
|
3;3;3;4
|
https://iclr.cc/virtual/2022/poster/7017
|
Sparse DETR: Efficient End-to-End Object Detection with Learnable Sparsity
|
https://github.com/kakaobrain/sparse-detr
| null | 3.25 | 5 |
Poster
|
5;5;5;5
|
2;3;4;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;2;3
| null | null | null |
GCN;efficient GCN;sampling
| null | 2.5 | null | null |
iclr
| -0.923381 | 0 | null |
main
| 4.75 |
3;5;5;6
|
3;3;3;3
| null |
Revisiting Layer-wise Sampling in Fast Training for Graph Convolutional Networks
| null | null | 3 | 3.5 |
Reject
|
5;3;4;2
|
2;3;2;3
|
null | null |
2022
| 1.75 | null | null | 0 | null | null | null |
1;2;2;2
| null | null | null |
Learning Theory
| null | 2 | null | null |
iclr
| -1 | 0.57735 | null |
main
| 3.5 |
3;3;3;5
|
2;3;2;3
| null |
Fairness-aware Federated Learning
| null | null | 2.5 | 3.5 |
Withdraw
|
4;4;4;2
|
2;2;2;2
|
null |
MSI3; Univ. Lyon, Inria, CNRS, ENS de Lyon, LIP UMR 5668; Univ. C ˆote d’Azur, Inria, Maasai, CNRS, LJAD; Univ. Bretagne-Suf, CNRS, IRISA; IP Paris, CMAP, UMR 7641
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6131; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Cédric Vincent-Cuaz, Rémi Flamary, Marco Corneli, Titouan Vayer, Nicolas Courty
|
https://iclr.cc/virtual/2022/poster/6131
|
Optimal Transport;Graph Learning
| null | 2.5 | null |
https://openreview.net/forum?id=RShaMexjc-x
|
iclr
| 0.4842 | 0.229416 | null |
main
| 6.25 |
5;6;6;8
|
4;3;3;4
|
https://iclr.cc/virtual/2022/poster/6131
|
Semi-relaxed Gromov-Wasserstein divergence and applications on graphs
| null | null | 3.5 | 3.25 |
Poster
|
3;2;4;4
|
3;2;2;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;2;3
| null | null | null | null | null | 2 | null | null |
iclr
| -0.471405 | 0.866025 | null |
main
| 5 |
3;5;6;6
|
2;3;4;3
| null |
Plug-In Inversion: Model-Agnostic Inversion for Vision with Data Augmentations
| null | null | 3 | 3.75 |
Reject
|
4;4;3;4
|
1;2;3;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;3;2;2
| null | null | null |
reinforcement learning;causality;confounding
| null | 2 | null | null |
iclr
| -0.333333 | 0 | null |
main
| 5.25 |
5;5;5;6
|
3;3;3;3
| null |
Causal Reinforcement Learning using Observational and Interventional Data
| null | null | 3 | 3.25 |
Reject
|
3;3;4;3
|
2;3;2;1
|
null |
Microsoft Research NYC; Microsoft Research NYC, Harvard University
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6790; None
| null | 0 | null | null | null |
3;3;3
| null |
Jordan Ash, Cyril Zhang, Surbhi Goel, Akshay Krishnamurthy, Sham M Kakade
|
https://iclr.cc/virtual/2022/poster/6790
|
deep reinforcement learning;reinforcement learning;bandits;exploration
| null | 3 | null |
https://openreview.net/forum?id=RXQ-FPbQYVn
|
iclr
| 0.755929 | 0.755929 | null |
main
| 6.333333 |
5;6;8
|
2;4;4
|
https://iclr.cc/virtual/2022/poster/6790
|
Anti-Concentrated Confidence Bonuses For Scalable Exploration
| null | null | 3.333333 | 3.666667 |
Poster
|
3;4;4
|
2;3;4
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;2;3;4
| null | null | null |
Explainable AI;Image Classification;Wavelets
| null | 2 | null | null |
iclr
| 0.555556 | 0.754337 | null |
main
| 4.25 |
3;3;5;6
|
2;2;4;3
| null |
Cartoon Explanations of Image Classifiers
| null | null | 2.75 | 3.75 |
Withdraw
|
3;4;4;4
|
1;2;2;3
|
null | null |
2022
| 3.25 | null | null | 0 | null | null | null |
3;3;3;4
| null | null | null |
low-rank matrix recovery;optimal transport;min-max optimization;permutation matrix
| null | 3.25 | null | null |
iclr
| -0.375823 | 0.911322 | null |
main
| 7.25 |
5;6;8;10
|
3;3;4;4
| null |
Low-rank Matrix Recovery with Unknown Correspondence
| null | null | 3.5 | 3.5 |
Reject
|
3;5;3;3
|
3;3;3;4
|
null |
Stanford University
|
2022
| 3.5 |
https://iclr.cc/virtual/2022/poster/6893; None
| null | 0 | null | null | null |
3;3;4;4
| null |
Sang Michael Xie, Aditi Raghunathan, Percy Liang, Tengyu Ma
|
https://iclr.cc/virtual/2022/poster/6893
|
in-context learning;language modeling;pre-training;GPT-3
| null | 2.75 | null |
https://openreview.net/forum?id=RdJVFCHjUMI
|
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6;6
|
4;4;3;3
|
https://iclr.cc/virtual/2022/poster/6893
|
An Explanation of In-context Learning as Implicit Bayesian Inference
|
https://github.com/
| null | 3.5 | 3.5 |
Poster
|
4;3;3;4
|
2;3;2;4
|
null |
University of Toronto & Vector Institute
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6901; None
| null | 0 | null | null | null |
3;3;3
| null |
Yangjun Ruan, Yann Dubois, Chris Maddison
|
https://iclr.cc/virtual/2022/poster/6901
|
distribution shift;domain generalization;representation learning;self-supervised learning;invariance;robustness
| null | 2.666667 | null |
https://openreview.net/forum?id=Rf58LPCwJj0
|
iclr
| 0 | 0.755929 | null |
main
| 6.333333 |
5;6;8
|
3;4;4
|
https://iclr.cc/virtual/2022/poster/6901
|
Optimal Representations for Covariate Shift
|
https://github.com/ryoungj/optdom
| null | 3.666667 | 3 |
Poster
|
3;3;3
|
2;3;3
|
null |
Huawei Noah’s Ark Lab; University of Padua; Tsinghua University
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6449; None
| null | 0 | null | null | null |
3;2;3;3
| null |
Wang Benyou, Yuxin Ren, Lifeng Shang, Xin Jiang, Qun Liu
|
https://iclr.cc/virtual/2022/poster/6449
|
pre-trained language models;tensor decomposition;compression;BERT
| null | 2.25 | null |
https://openreview.net/forum?id=RftryyYyjiG
|
iclr
| 0.333333 | 0.57735 | null |
main
| 5.75 |
5;6;6;6
|
2;2;3;3
|
https://iclr.cc/virtual/2022/poster/6449
|
Exploring extreme parameter compression for pre-trained language models
|
https://github.com/twinkle0331/Xcompression
| null | 2.5 | 4.25 |
Poster
|
4;4;5;4
|
1;3;2;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
compositional generalization;transformer;compositionality;deep learning;NLP
| null | 1.25 | null | null |
iclr
| 1 | 0.333333 | null |
main
| 3.5 |
3;3;3;5
|
3;2;3;3
| null |
Iterative Decoding for Compositional Generalization in Transformers
| null | null | 2.75 | 4.25 |
Reject
|
4;4;4;5
|
1;0;2;2
|
null |
Imperial College London; InsightFace; Huawei
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6369; None
| null | 0 | null | null | null |
2;2;4;3
| null |
Jia Guo, Jiankang Deng, Alexandros Lattas, Stefanos Zafeiriou
|
https://iclr.cc/virtual/2022/poster/6369
|
efficient face detection;computation redistribution;sample redistribution
| null | 3.25 | null |
https://openreview.net/forum?id=RhB1AdoFfGE
|
iclr
| 0 | 1 | null |
main
| 7 |
6;6;8;8
|
3;3;4;4
|
https://iclr.cc/virtual/2022/poster/6369
|
Sample and Computation Redistribution for Efficient Face Detection
|
https://github.com/deepinsight/insightface/tree/master/detection/scrfd
| null | 3.5 | 3 |
Poster
|
3;3;3;3
|
3;3;4;3
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;3;3
| null | null | null | null | null | 2.666667 | null | null |
iclr
| 1 | 0 | null |
main
| 4.333333 |
3;5;5
|
3;4;2
| null |
Contrastive Embeddings for Neural Architectures
| null | null | 3 | 3.666667 |
Reject
|
3;4;4
|
3;3;2
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
3;2;3
| null | null | null |
reward imputation;bandit;sketching;regret analysis
| null | 3 | null | null |
iclr
| 0 | 0.866025 | null |
main
| 5.333333 |
5;5;6
|
2;3;4
| null |
Partial Information as Full: Reward Imputation with Sketching in Bandits
| null | null | 3 | 4 |
Reject
|
4;4;4
|
3;3;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
3;3;3;2
| null | null | null |
Transformer;Domain Adaption;Medical;Clinical;Attention
| null | 3.25 | null | null |
iclr
| -0.707107 | 0.57735 | null |
main
| 5.5 |
5;5;6;6
|
3;3;4;3
| null |
KIMERA: Injecting Domain Knowledge into Vacant Transformer Heads
| null | null | 3.25 | 4 |
Withdraw
|
4;5;4;3
|
3;3;4;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
exploration;reinforcement learning;action-value methods;soft-greedy operator;softmax;mellowmax;epsilon-greedy;suboptimality gap
| null | 2.25 | null | null |
iclr
| 0.288675 | 0 | null |
main
| 5 |
3;5;6;6
|
3;3;3;3
| null |
Resmax: An Alternative Soft-Greedy Operator for Reinforcement Learning
| null | null | 3 | 4 |
Reject
|
4;3;4;5
|
2;2;3;2
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
3;3;2;3
| null | null | null |
Model Compression;NAS;Neural Network Acceleration
| null | 2.25 | null | null |
iclr
| -0.132453 | 0.789474 | null |
main
| 4.75 |
3;5;5;6
|
1;3;4;3
| null |
Hardware-Aware Network Transformation
| null | null | 2.75 | 3.75 |
Withdraw
|
4;3;4;4
|
1;2;3;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
activation functions;adversarial training
| null | 2.25 | null | null |
iclr
| 0.333333 | 0.816497 | null |
main
| 4.5 |
3;5;5;5
|
2;3;3;4
| null |
Parameterizing Activation Functions for Adversarial Robustness
| null | null | 3 | 4.25 |
Withdraw
|
4;4;5;4
|
1;3;3;2
|
null |
Department of Statistics & Data Science, Machine Learning Department, Carnegie Mellon University
|
2022
| 2.6 |
https://iclr.cc/virtual/2022/poster/6896; None
| null | 0 | null | null | null |
3;2;2;4;2
| null |
Aleksandr Podkopaev, Aaditya Ramdas
|
https://iclr.cc/virtual/2022/poster/6896
|
Distribution shift;sequential testing
| null | 2.8 | null |
https://openreview.net/forum?id=Ro_zAjZppv
|
iclr
| 0.645497 | 0.408248 | null |
main
| 6.8 |
6;6;6;8;8
|
4;4;3;4;4
|
https://iclr.cc/virtual/2022/poster/6896
|
Tracking the risk of a deployed model and detecting harmful distribution shifts
| null | null | 3.8 | 3 |
Poster
|
2;3;3;3;4
|
3;2;2;3;4
|
null |
Intel Labs; University of Copenhagen; Cornell University, Cornell Tech; Cornell University; Apple
|
2022
| 2.666667 |
https://iclr.cc/virtual/2022/poster/6809; None
| null | 0 | null | null | null |
3;2;3
| null |
Boyi Li, Kilian Weinberger, Serge Belongie, Vladlen Koltun, Rene Ranftl
|
https://iclr.cc/virtual/2022/poster/6809
|
language-driven;semantic segmentation;zero-shot;transformer
| null | 3 | null |
https://openreview.net/forum?id=RriDjddCLN
|
iclr
| -0.755929 | 0.755929 | null |
main
| 6.333333 |
5;6;8
|
2;4;4
|
https://iclr.cc/virtual/2022/poster/6809
|
Language-driven Semantic Segmentation
|
https://github.com/isl-org/lang-seg
| null | 3.333333 | 3.333333 |
Poster
|
4;3;3
|
3;3;3
|
null |
Dept. of Computer Science, Johns Hopkins University; Toyota Tech. Institute at Chicago; Dept. of Computer Science, Columbia University
|
2022
| 2.25 |
https://iclr.cc/virtual/2022/poster/6600; None
| null | 0 | null | null | null |
2;2;2;3
| null |
Hongyuan Mei, Chenghao Yang, Jason Eisner
|
https://iclr.cc/virtual/2022/poster/6600
|
irregular time series;generative Transformers;neuro-symbolic architectures;logic programming
| null | 2.25 | null |
https://openreview.net/forum?id=Rty5g9imm7H
|
iclr
| 0 | -0.648886 | null |
main
| 4.75 |
3;5;5;6
|
4;3;2;3
|
https://iclr.cc/virtual/2022/poster/6600
|
Transformer Embeddings of Irregularly Spaced Events and Their Participants
| null | null | 3 | 3 |
Poster
|
3;4;2;3
|
2;2;2;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
Automatic Data Augmentation;Multi-Agent Reinforcement Learning
| null | 2.5 | null | null |
iclr
| -0.57735 | 0.57735 | null |
main
| 5.75 |
5;6;6;6
|
3;3;4;4
| null |
Local Patch AutoAugment with Multi-Agent Collaboration
| null | null | 3.5 | 3.5 |
Reject
|
4;4;3;3
|
2;3;2;3
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;2;3
| null | null | null |
3D Representation Learning;3D Self-supervised Learning
| null | 1.666667 | null | null |
iclr
| -0.981981 | 0 | null |
main
| 4.666667 |
3;5;6
|
3;3;3
| null |
Self-Supervised Modality-Invariant and Modality-Specific Feature Learning for 3D Objects
| null | null | 3 | 4 |
Withdraw
|
5;4;3
|
0;2;3
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;3;2;4
| null | null | null |
graph neurals networks;graph classification;probabilistic models
| null | 2.5 | null | null |
iclr
| 0 | 0.57735 | null |
main
| 5.75 |
5;5;5;8
|
3;3;4;4
| null |
The Infinite Contextual Graph Markov Model
| null | null | 3.5 | 3 |
Reject
|
2;3;4;3
|
2;2;2;4
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
3;2;3;3
| null | null | null | null | null | 2.75 | null | null |
iclr
| 0.816497 | 0 | null |
main
| 6.5 |
6;6;6;8
|
3;3;3;3
| null |
Lottery Image Prior
| null | null | 3 | 4 |
Reject
|
4;3;4;5
|
2;3;3;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;2;3;4
| null | null | null | null | null | 2.5 | null | null |
iclr
| 0.800641 | 0.83205 | null |
main
| 5.5 |
3;5;6;8
|
2;2;4;4
| null |
Coherent and Consistent Relational Transfer Learning with Autoencoders
| null | null | 3 | 3.75 |
Reject
|
3;4;4;4
|
2;2;3;3
|
null |
Center for Machine Vision and Signal Analysis, University of Oulu, Finland; School of Computer Science, Institute for Research in Fundamental Sciences (IPM)
|
2022
| 2.333333 |
https://iclr.cc/virtual/2022/poster/6430; None
| null | 0 | null | null | null |
2;3;2
| null |
Mozhgan Pourkeshavarz, Guoying Zhao, Mohammad Sabokrou
|
https://iclr.cc/virtual/2022/poster/6430
|
Deepl Learning;Class Incremental learning;Continual learning;Experiences
| null | 2.666667 | null |
https://openreview.net/forum?id=RxplU3vmBx
|
iclr
| 0.5 | 0 | null |
main
| 6.666667 |
6;6;8
|
3;3;3
|
https://iclr.cc/virtual/2022/poster/6430
|
Looking Back on Learned Experiences For Class/task Incremental Learning
|
https://github.com/MozhganPourKeshavarz/Cost-Free-Incremental-Learning
| null | 3 | 3.666667 |
Spotlight
|
3;4;4
|
2;3;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
3;1;2;3
| null | null | null |
Semi-Supervised Learning;Object Detection
| null | 2.5 | null | null |
iclr
| -0.333333 | 0.57735 | null |
main
| 5.25 |
5;5;5;6
|
3;4;3;4
| null |
Scale-Invariant Teaching for Semi-Supervised Object Detection
| null | null | 3.5 | 4.25 |
Withdraw
|
4;4;5;4
|
2;3;2;3
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
2;3;3
| null | null | null |
Continual learning;Prompt-based learning
| null | 2.333333 | null | null |
iclr
| 1 | 0 | null |
main
| 4.333333 |
3;5;5
|
3;3;3
| null |
Learning to Prompt for Continual Learning
| null | null | 3 | 3.666667 |
Withdraw
|
3;4;4
|
2;2;3
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;3;3;3
| null | null | null |
robustness;common corruptions;adversarial examples;robust vision;vision science
| null | 2.25 | null | null |
iclr
| -0.57735 | 0.522233 | null |
main
| 4.5 |
3;5;5;5
|
2;3;2;4
| null |
Geon3D: Exploiting 3D Shape Bias towards Building Robust Machine Vision
| null | null | 2.75 | 3.5 |
Withdraw
|
4;3;4;3
|
2;2;2;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
3;1;3;3
| null | null | null |
Contrastive learning;Domain generalization;Speech Synthesis;Diffusion Probabilistic Models
| null | 2 | null | null |
iclr
| -0.57735 | 0.57735 | null |
main
| 4 |
3;3;5;5
|
3;1;3;3
| null |
SynCLR: A Synthesis Framework for Contrastive Learning of out-of-domain Speech Representations
| null | null | 2.5 | 4.25 |
Withdraw
|
4;5;4;4
|
3;1;2;2
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
3;2;3;3
| null | null | null |
Deep Reinforcement Learning;Generalization in Reinforcement Learning
| null | 2.25 | null | null |
iclr
| 0.408248 | 0.816497 | null |
main
| 6 |
5;5;6;8
|
3;3;4;4
| null |
Adversarial Style Transfer for Robust Policy Optimization in Reinforcement Learning
| null | null | 3.5 | 4 |
Reject
|
5;3;3;5
|
2;2;3;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
machine learning;active learning;uncertainty;hypothesis perturbation;disagreement region
| null | 2.25 | null | null |
iclr
| -0.57735 | 1 | null |
main
| 4 |
1;5;5;5
|
1;3;3;3
| null |
Active Learning: Sampling in the Least Probable Disagreement Region
| null | null | 2.5 | 3.5 |
Withdraw
|
4;3;3;4
|
2;2;3;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2
| null | null | null |
Graph;Graph Neural Network;Convex;Input-convex;Implicit function theorem.
| null | 2.333333 | null | null |
iclr
| 0.5 | 0 | null |
main
| 5.333333 |
5;5;6
|
3;3;3
| null |
Input Convex Graph Neural Networks: An Application to Optimal Control and Design Optimization
| null | null | 3 | 2.666667 |
Withdraw
|
2;3;3
|
2;2;3
|
null |
Under double-blind review
|
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
emergent communication;compositionality;metrics;language model
| null | 2.5 | null | null |
iclr
| 0 | 0 | null |
main
| 4 |
3;3;5;5
|
2;3;2;3
| null |
Icy: A benchmark for measuring compositional inductive bias of emergent communication models
| null | null | 2.5 | 3.5 |
Withdraw
|
4;3;3;4
|
2;2;2;4
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;2;3
| null | null | null | null | null | 2.333333 | null | null |
iclr
| -0.866025 | 0 | null |
main
| 5 |
3;6;6
|
3;3;3
| null |
Value-aware transformers for 1.5d data
| null | null | 3 | 4 |
Reject
|
5;3;4
|
2;2;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
Hypercomplex Neural Networks;Lightweight Neural Networks;Quaternion Neural Networks;Parameterized Hypercomplex Convolutions;Hypercomplex Representation Learning
| null | 2.5 | null | null |
iclr
| 0.749269 | 0.288675 | null |
main
| 6 |
5;5;6;8
|
3;2;4;3
| null |
Lightweight Convolutional Neural Networks By Hypercomplex Parameterization
| null | null | 3 | 3.75 |
Reject
|
4;2;4;5
|
2;2;3;3
|
null | null |
2022
| 2.2 | null | null | 0 | null | null | null |
2;2;2;2;3
| null | null | null |
domain adaptation;small target dataset;communication autoencoders;mixture density networks;wireless channel
| null | 2 | null | null |
iclr
| 0.272166 | 0.272166 | null |
main
| 4.4 |
3;3;5;5;6
|
3;2;3;2;3
| null |
Fast and Sample-Efficient Domain Adaptation for Autoencoder-Based End-to-End Communication
| null | null | 2.6 | 3.6 |
Reject
|
3;4;4;3;4
|
2;2;2;2;2
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
Deep Learning;Bayesian;Uncertainty;Testbed;Opensource Code
| null | 3 | null | null |
iclr
| 0.57735 | 0.57735 | null |
main
| 5.5 |
5;5;6;6
|
4;3;4;4
| null |
Evaluating Predictive Distributions: Does Bayesian Deep Learning Work?
|
https://anonymous.4open.science/r/neural-testbed-B839
| null | 3.75 | 3.75 |
Reject
|
4;3;4;4
|
2;3;3;4
|
null |
Carnegie Mellon University; UC Berkeley
|
2022
| 2 |
https://iclr.cc/virtual/2022/poster/6088; None
| null | 0 | null | null | null |
2;3;2;1
| null |
Scott Emmons, Benjamin Eysenbach, Ilya Kostrikov, Sergey Levine
|
https://iclr.cc/virtual/2022/poster/6088
|
reinforcement learning;deep reinforcement learning;offline reinforcement learning
| null | 2.5 | null |
https://openreview.net/forum?id=S874XAIpkR-
|
iclr
| 0.648886 | 0.927173 | null |
main
| 6.25 |
5;6;6;8
|
3;3;3;4
|
https://iclr.cc/virtual/2022/poster/6088
|
RvS: What is Essential for Offline RL via Supervised Learning?
|
https://github.com/scottemmons/rvs
| null | 3.25 | 3 |
Poster
|
3;2;3;4
|
2;3;3;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
1;2;1;4
| null | null | null |
Shortcut Learning;Bias;Classification;Imbalanced Classification;Robustness
| null | 2.25 | null | null |
iclr
| -0.32063 | 0.725589 | null |
main
| 4.25 |
1;3;5;8
|
1;3;3;3
| null |
White Paper Assistance: A Step Forward Beyond the Shortcut Learning
| null | null | 2.5 | 3.75 |
Reject
|
5;3;3;4
|
1;2;3;3
|
null | null |
2022
| 2.4 | null | null | 0 | null | null | null |
2;3;3;2;2
| null | null | null |
Language Model;Knowledge;Multilingual
| null | 2.4 | null | null |
iclr
| -0.763763 | 0.645497 | null |
main
| 4.2 |
3;3;5;5;5
|
3;2;3;4;3
| null |
Knowledge Based Multilingual Language Model
| null | null | 3 | 3.8 |
Reject
|
4;5;3;3;4
|
3;1;3;3;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
3;2;2;2
| null | null | null |
Self-supervised Learning;Learnability;Intrinsic Dimension;Representation Learning
| null | 1.75 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
5;5;5;5
|
3;3;3;2
| null |
Learnability and Expressiveness in Self-Supervised Learning
| null | null | 2.75 | 3.25 |
Reject
|
3;3;4;3
|
3;2;0;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2
| null | null | null |
Domain Generalization;latent disentanglement;Image classification;Image to Image translation
| null | 2 | null | null |
iclr
| -0.5 | 1 | null |
main
| 4.333333 |
3;5;5
|
3;4;4
| null |
Latent Feature Disentanglement For Visual Domain Generalization
| null | null | 3.666667 | 3.666667 |
Withdraw
|
4;4;3
|
2;2;2
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;2;3
| null | null | null |
federated learning;personalization;spurious features
| null | 1.666667 | null | null |
iclr
| -1 | 0.866025 | null |
main
| 4 |
3;3;6
|
3;2;4
| null |
Robust and Personalized Federated Learning with Spurious Features: an Adversarial Approach
| null | null | 3 | 3.666667 |
Reject
|
4;4;3
|
0;2;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2
| null | null | null | null | null | 2.666667 | null | null |
iclr
| 0 | 1 | null |
main
| 4.333333 |
3;5;5
|
2;3;3
| null |
PNODE: A memory-efficient neural ODE framework based on high-level adjoint differentiation
| null | null | 2.666667 | 4 |
Withdraw
|
4;4;4
|
2;3;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
1;2;3;3
| null | null | null |
network subspace;compression;post-training;pruning;quantization;efficient
| null | 2.25 | null | null |
iclr
| 0 | 0.333333 | null |
main
| 4.25 |
3;3;3;8
|
3;2;3;3
| null |
LCS: Learning Compressible Subspaces for Adaptive Network Compression at Inference Time
| null | null | 2.75 | 4 |
Reject
|
4;4;4;4
|
2;1;3;3
|
null |
Department of Computer Science and Engineering, University of Texas at Arlington; Institute for AI Industry Research (AIR), Tsinghua University; Beijing National Research Center for Information Science and Technology (BNRist), Department of Computer Science and Technology, Tsinghua University; Tencent AI Lab
|
2022
| 2.25 |
https://iclr.cc/virtual/2022/poster/6795; None
| null | 0 | null | null | null |
1;3;3;2
| null |
Wenbing Huang, Jiaqi Han, Yu Rong, Tingyang Xu, Fuchun Sun, Junzhou Huang
|
https://iclr.cc/virtual/2022/poster/6795
| null | null | 2.25 | null |
https://openreview.net/forum?id=SHbhHHfePhP
|
iclr
| 0.522233 | 0 | null |
main
| 6.75 |
5;6;8;8
|
4;4;4;4
|
https://iclr.cc/virtual/2022/poster/6795
|
Equivariant Graph Mechanics Networks with Constraints
| null | null | 4 | 3.25 |
Poster
|
2;4;4;3
|
1;2;3;3
|
null | null |
2022
| 2.6 | null | null | 0 | null | null | null |
2;2;3;3;3
| null | null | null |
few-shot learning;prime-dual network;self-supervision
| null | 3 | null | null |
iclr
| 0.25 | 0.534522 | null |
main
| 5.8 |
5;6;6;6;6
|
2;4;3;3;2
| null |
Self-Supervised Prime-Dual Networks for Few-Shot Image Classification
| null | null | 2.8 | 3.2 |
Reject
|
3;3;3;3;4
|
3;3;3;3;3
|
null |
IBM Research, Yorktown Heights; Rensselaer Polytechnic Institute, New York
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6166; None
| null | 0 | null | null | null |
3;3;3;3
| null |
Keerthiram Murugesan, Vijay Sadashivaiah, Ronny Luss, Karthikeyan Shanmugam, Pin-Yu Chen, Amit Dhurandhar
|
https://iclr.cc/virtual/2022/poster/6166
|
Feature routing;Transferable Representations
| null | 2.75 | null |
https://openreview.net/forum?id=SIKV0_MrZlr
|
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6;6
|
2;3;2;4
|
https://iclr.cc/virtual/2022/poster/6166
|
Auto-Transfer: Learning to Route Transferable Representations
|
https://github.com/IBM/auto-transfer
| null | 2.75 | 4.25 |
Poster
|
5;5;3;4
|
3;3;2;3
|
null | null |
2022
| 0 | null | null | 0 | null | null | null | null | null | null | null |
missingness;imputation;mHealth;sensors;transformer;self-attention
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 0 | null | null | null |
PulseImpute: A Novel Benchmark Task and Architecture for Imputation of Physiological Signals
| null | null | 0 | 0 |
Withdraw
| null | null |
null |
(No affiliation provided in the text)
|
2022
| 3.333333 |
https://iclr.cc/virtual/2022/poster/6441; None
| null | 0 | null | null | null |
4;3;3
| null |
Raphaël Dang-Nhu
|
https://iclr.cc/virtual/2022/poster/6441
| null | null | 2.666667 | null |
https://openreview.net/forum?id=SLz5sZjacp
|
iclr
| 0 | 0 |
(Not provided in the text)
|
main
| 6 |
6;6;6
|
3;3;3
|
https://iclr.cc/virtual/2022/poster/6441
|
Evaluating Disentanglement of Structured Representations
|
(Not provided in the text)
| null | 3 | 4 |
Poster
|
5;3;4
|
2;3;3
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;2;3
| null | null | null |
Text-to-Image Generation;Computer Vision
| null | 2 | null | null |
iclr
| 0 | 1 | null |
main
| 5.333333 |
5;5;6
|
3;3;4
| null |
Multi-Tailed, Multi-Headed, Spatial Dynamic Memory refined Text-to-Image Synthesis
| null | null | 3.333333 | 4 |
Reject
|
4;4;4
|
2;2;2
|
null |
Max Planck Institute for Intelligent Systems, Tübingen, Germany and Computational and Biological Learning Group, University of Cambridge; Facebook Reality Labs; DeepMind
|
2022
| 2 |
https://iclr.cc/virtual/2022/poster/6195; None
| null | 0 | null | null | null |
2;1;2;3
| null |
Arunkumar Byravan, Leonard Hasenclever, Piotr Trochim, Mehdi Mirza, Alessandro Ialongo, Yuval Tassa, Jost Tobias Springenberg, Abbas Abdolmaleki, Nicolas Heess, Josh Merel, Martin Riedmiller
|
https://iclr.cc/virtual/2022/poster/6195
|
Model-based Reinforcement Learning;Planning;Robotics;Model Predictive Control;Learning
| null | 2.75 | null |
https://openreview.net/forum?id=SS8F6tFX3-
|
iclr
| 0.333333 | 0.333333 | null |
main
| 6.5 |
6;6;6;8
|
3;4;4;4
|
https://iclr.cc/virtual/2022/poster/6195
|
Evaluating Model-Based Planning and Planner Amortization for Continuous Control
| null | null | 3.75 | 3.75 |
Poster
|
4;3;4;4
|
2;2;3;4
|
null |
Affiliation not provided
|
2022
| 3.2 | null | null | 0 | null | null | null |
3;3;3;4;3
| null | null | null |
identity disentanglement;contrastive learning;data augmentation;self-supervised learning
| null | 3 | null | null |
iclr
| -0.408248 | 0.872872 | null |
main
| 5.4 |
5;5;5;6;6
|
3;2;3;4;4
| null |
Identity-Disentangled Adversarial Augmentation for Self-supervised Learning
| null | null | 3.2 | 3.4 |
Reject
|
4;3;4;4;2
|
2;3;3;4;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;2;3
| null | null | null |
deep learning optimization;automatic learning rate drop;schedules of the hyperparameters
| null | 2.25 | null | null |
iclr
| 0 | 0 | null |
main
| 3 |
3;3;3;3
|
3;3;1;2
| null |
AutoDrop: Training Deep Learning Models with Automatic Learning Rate Drop
| null | null | 2.25 | 4 |
Withdraw
|
4;4;4;4
|
3;2;2;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
adversarial robustness;representation learning
| null | 2.25 | null | null |
iclr
| -0.688247 | 0 | null |
main
| 4 |
3;3;5;5
|
4;3;4;3
| null |
Adversarial Robustness as a Prior for Learned Representations
|
https://github.com/cantankerousdolphin/robust-learned-representations
| null | 3.5 | 3.75 |
Reject
|
4;5;4;2
|
2;2;2;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
Graph Convolutional Network;graph regularization;GNN initialization;graph-based PCA
| null | 2.5 | null | null |
iclr
| -0.816497 | 0.522233 | null |
main
| 5.25 |
5;5;5;6
|
4;3;2;4
| null |
Connecting Graph Convolution and Graph PCA
| null | null | 3.25 | 4 |
Reject
|
4;5;4;3
|
2;2;4;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
1;3;2;3
| null | null | null |
unsupervised;machine translation;language modeling;few-shot learning
| null | 1.25 | null | null |
iclr
| -0.622543 | -0.132453 | null |
main
| 4.75 |
3;5;5;6
|
3;3;1;3
| null |
Unsupervised Neural Machine Translation with Generative Language Models Only
| null | null | 2.5 | 3.75 |
Reject
|
5;3;3;4
|
0;3;2;0
|
null |
MIT CSAIL; CISPA Helmholtz Center for Information Security; Harvard T.H. Chan School of Public Health
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/6834; None
| null | 0 | null | null | null |
2;3;2;3
| null |
Rebekka Burkholz, Nilanjana Laha, Rajarshi Mukherjee, Alkis Gotovos
|
https://iclr.cc/virtual/2022/poster/6834
|
theory;deep learning;lottery tickets;universality
| null | 1.25 | null |
https://openreview.net/forum?id=SYB4WrJql1n
|
iclr
| 0.816497 | 0.57735 | null |
main
| 6.5 |
6;6;6;8
|
4;3;3;4
|
https://iclr.cc/virtual/2022/poster/6834
|
On the Existence of Universal Lottery Tickets
| null | null | 3.5 | 3 |
Poster
|
3;3;2;4
|
0;3;0;2
|
null |
University of Texas at Austin; University of Science and Technology of China; University of California, Irvine
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6147; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Tianlong Chen, Zhenyu Zhang, pengjun wang, Santosh Balachandra, Haoyu Ma, Zehao Wang, Zhangyang Wang
|
https://iclr.cc/virtual/2022/poster/6147
| null | null | 3.5 | null |
https://openreview.net/forum?id=SYuJXrXq8tw
|
iclr
| 0.777778 | 0.777778 | null |
main
| 6.75 |
5;6;8;8
|
3;4;4;4
|
https://iclr.cc/virtual/2022/poster/6147
|
Sparsity Winning Twice: Better Robust Generalization from More Efficient Training
|
https://github.com/VITA-Group/Sparsity-Win-Robust-Generalization
| null | 3.75 | 3.75 |
Poster
|
3;4;4;4
|
2;4;4;4
|
null | null |
2022
| 3.25 | null | null | 0 | null | null | null |
3;3;4;3
| null | null | null |
active learning;Bayesian active learning;batch active learning
| null | 2.25 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
5;5;5;5
|
3;3;4;4
| null |
SABAL: Sparse Approximation-based Batch Active Learning
| null | null | 3.5 | 4 |
Reject
|
4;4;4;4
|
2;2;3;2
|
null |
MIT, Microsoft; MIT; MIT, Google; Cornell University, Google; Cornell University
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6068; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Mark Hamilton, Zhoutong Zhang, Bharath Hariharan, Noah Snavely, William Freeman
|
https://iclr.cc/virtual/2022/poster/6068
|
Unsupervised Semantic Segmentation;Unsupervised Learning;Deep Features;Contrastive Learning;Visual Transformers;Cocostuff;Cityscapes;Semantic Segmentation
| null | 2.5 | null |
https://openreview.net/forum?id=SaKO6z6Hl0c
|
iclr
| 0.57735 | 0 | null |
main
| 7 |
6;6;8;8
|
3;4;3;4
|
https://iclr.cc/virtual/2022/poster/6068
|
Unsupervised Semantic Segmentation by Distilling Feature Correspondences
| null | null | 3.5 | 3.5 |
Poster
|
2;4;4;4
|
2;3;2;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
Federated Learning;Split Learning
| null | 3 | null | null |
iclr
| 0 | 0.942809 | null |
main
| 5 |
3;5;6;6
|
2;3;3;3
| null |
Accelerating Federated Split Learning via Local-Loss-Based Training
| null | null | 2.75 | 4 |
Withdraw
|
4;4;4;4
|
2;3;3;4
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
data-oriented design;computer vision;scene recognition;image recognition
| null | 1.75 | null | null |
iclr
| 0 | 0.816497 | null |
main
| 3.5 |
3;3;3;5
|
2;1;2;3
| null |
Data-oriented Scene Recognition
| null | null | 2 | 4 |
Reject
|
4;4;4;4
|
2;1;2;2
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;2;3
| null | null | null | null | null | 2.666667 | null | null |
iclr
| 0.866025 | 1 | null |
main
| 4.333333 |
3;5;5
|
2;3;3
| null |
Soteria: In search of efficient neural networks for private inference
| null | null | 2.666667 | 3 |
Reject
|
2;3;4
|
3;2;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
3;2;2;4
| null | null | null |
feedback alignement;optimization;convergence guarantees;implicit regularization
| null | 1 | null | null |
iclr
| 0.870388 | 0 | null |
main
| 5.75 |
5;5;5;8
|
4;4;4;4
| null |
Convergence Analysis and Implicit Regularization of Feedback Alignment for Deep Linear Networks
| null | null | 4 | 3.75 |
Reject
|
4;3;3;5
|
2;0;2;0
|
null | null |
2022
| 1.75 | null | null | 0 | null | null | null |
2;1;1;3
| null | null | null |
Temporal Attention;Temporal Knowledge Graph Reasoning;Knowledge Graph Completion;Entity Alignment
| null | 2.25 | null | null |
iclr
| 0.688247 | 0 | null |
main
| 4.75 |
3;5;5;6
|
3;3;3;3
| null |
Time-aware Relational Graph Attention Network for Temporal Knowledge Graph Embeddings
| null | null | 3 | 3.5 |
Withdraw
|
3;4;3;4
|
2;2;2;3
|
null | null |
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6961; None
| null | 0 | null | null | null |
3;3;3
| null |
Xiaoyu Chen, Jiachen Hu, Lin Yang, Liwei Wang
|
https://iclr.cc/virtual/2022/poster/6961
|
reward-free exploration;model-based reinforcement learning;learning theory
| null | 1.333333 | null |
https://openreview.net/forum?id=SidzxAb9k30
|
iclr
| -0.5 | 0.5 | null |
main
| 7.333333 |
6;8;8
|
3;4;3
|
https://iclr.cc/virtual/2022/poster/6961
|
Near-Optimal Reward-Free Exploration for Linear Mixture MDPs with Plug-in Solver
| null | null | 3.333333 | 2.666667 |
Spotlight
|
3;3;2
|
3;1;0
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
Reinforcement learning theory;autonomous exploration
| null | 1 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
3;5;6;6
|
3;2;3;3
| null |
Near-Optimal Algorithms for Autonomous Exploration and Multi-Goal Stochastic Shortest Path
| null | null | 2.75 | 3 |
Reject
|
3;3;3;3
|
1;0;3;0
|
null | null |
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6569; None
| null | 0 | null | null | null |
3;3;3
| null |
Dmitry Baranchuk, Andrey Voynov, Ivan Rubachev, Valentin Khrulkov, Artem Babenko
|
https://iclr.cc/virtual/2022/poster/6569
| null | null | 3 | null |
https://openreview.net/forum?id=SlxSY2UZQT
|
iclr
| -0.5 | -1 | null |
main
| 7.333333 |
6;8;8
|
4;3;3
|
https://iclr.cc/virtual/2022/poster/6569
|
Label-Efficient Semantic Segmentation with Diffusion Models
| null | null | 3.333333 | 3.666667 |
Poster
|
4;3;4
|
3;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
1;2;2;3
| null | null | null |
Generative Models;Molecular Graphs;3D Molecules;Drug Discovery;Equivariance
| null | 2.25 | null | null |
iclr
| -0.688247 | 0 | null |
main
| 4.75 |
3;5;5;6
|
3;3;3;3
| null |
Generating Realistic 3D Molecules with an Equivariant Conditional Likelihood Model
| null | null | 3 | 3.5 |
Reject
|
4;4;3;3
|
2;2;2;3
|
null | null |
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/7159; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Ian Gemp, Brian McWilliams, Claire Vernade, Thore Graepel
|
https://iclr.cc/virtual/2022/poster/7159
|
pca;principal components analysis;nash;games;eigendecomposition;svd;singular value decomposition
| null | 3 | null |
https://openreview.net/forum?id=So6YAqnqgMj
|
iclr
| 0.57735 | 0 | null |
main
| 6.5 |
5;5;8;8
|
4;4;4;4
|
https://iclr.cc/virtual/2022/poster/7159
|
EigenGame Unloaded: When playing games is better than optimizing
| null | null | 4 | 3.25 |
Poster
|
3;3;4;3
|
3;3;3;3
|
null | null |
2022
| 2.6 | null | null | 0 | null | null | null |
3;3;2;2;3
| null | null | null |
computer vision;3d detection;multi-modal;point clouds
| null | 2.8 | null | null |
iclr
| 0.666667 | 0.645497 | null |
main
| 5.4 |
5;5;5;6;6
|
3;3;2;4;3
| null |
Sparse Fuse Dense: Towards High Quality 3D Detection With Depth Completion
| null | null | 3 | 3.6 |
Withdraw
|
4;3;3;4;4
|
4;2;3;2;3
|
null | null |
2022
| 2.8 |
https://iclr.cc/virtual/2022/poster/5956; None
| null | 0 | null | null | null |
2;3;4;2;3
| null |
David Bertoin, Emmanuel Rachelson
|
https://iclr.cc/virtual/2022/poster/5956
|
Reinforcement learning;Generalization;Regularization
| null | 3 | null |
https://openreview.net/forum?id=Sq0-tgDyHe4
|
iclr
| -0.25 | 0.408248 | null |
main
| 7.6 |
6;8;8;8;8
|
3;4;3;3;4
|
https://iclr.cc/virtual/2022/poster/5956
|
Local Feature Swapping for Generalization in Reinforcement Learning
| null | null | 3.4 | 3.8 |
Poster
|
4;4;4;4;3
|
3;3;3;3;3
|
null | null |
2022
| 2.6 | null | null | 0 | null | null | null |
2;3;3;2;3
| null | null | null |
Physical neural network;extrapolation
| null | 2 | null | null |
iclr
| 0.322749 | 0.790569 | null |
main
| 4 |
3;3;3;5;6
|
2;2;2;2;4
| null |
WHAT TO DO IF SPARSE REPRESENTATION LEARNING FAILS UNEXPECTEDLY?
| null | null | 2.4 | 3.4 |
Reject
|
4;3;3;3;4
|
2;2;2;2;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;3;2
| null | null | null |
weakly-supervised object detection;vision and language;representation learning
| null | 1.75 | null | null |
iclr
| -0.57735 | -0.707107 | null |
main
| 4 |
3;3;5;5
|
3;4;2;3
| null |
Learning Better Visual Representations for Weakly-Supervised Object Detection Using Natural Language Supervision
| null | null | 3 | 3.75 |
Withdraw
|
4;4;3;4
|
2;1;2;2
|
null | null |
2022
| 2.666667 |
https://iclr.cc/virtual/2022/poster/6517; None
| null | 0 | null | null | null |
2;3;3
| null |
Alexis Bellot, Kim Branson, Mihaela van der Schaar
|
https://iclr.cc/virtual/2022/poster/6517
|
Dynamical systems;graphical modelling;structure learning
| null | 2.666667 | null |
https://openreview.net/forum?id=SsHBkfeRF9L
|
iclr
| -1 | 0 | null |
main
| 6 |
5;5;8
|
4;4;4
|
https://iclr.cc/virtual/2022/poster/6517
|
Neural graphical modelling in continuous-time: consistency guarantees and algorithms
| null | null | 4 | 3.666667 |
Poster
|
4;4;3
|
2;3;3
|
null | null |
2022
| 3 |
https://iclr.cc/virtual/2022/poster/7146; None
| null | 0 | null | null | null |
2;3;4;3
| null |
Chu-Cheng Lin & Arya D. McCarthy
|
https://iclr.cc/virtual/2022/poster/7146
|
energy-based models;turing completeness;model capacity;sequence models;autoregressive models;partition function;parameter estimation;model selection
| null | 0.75 | null |
https://openreview.net/forum?id=SsPCtEY6yCl
|
iclr
| 0.57735 | -0.57735 | null |
main
| 7 |
6;6;8;8
|
4;4;4;3
|
https://iclr.cc/virtual/2022/poster/7146
|
On the Uncomputability of Partition Functions in Energy-Based Sequence Models
| null | null | 3.75 | 3.25 |
Spotlight
|
3;3;3;4
|
0;0;1;2
|
null | null |
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6657; None
| null | 0 | null | null | null |
3;3;3;3
| null |
Yu Zheng, Zhi Zhang, Shen Yan, Mi Zhang
|
https://iclr.cc/virtual/2022/poster/6657
|
automated machine learning;data augmentation
| null | 2.75 | null |
https://openreview.net/forum?id=St-53J9ZARf
|
iclr
| -0.870388 | 0.816497 | null |
main
| 6.75 |
5;6;8;8
|
2;3;4;3
|
https://iclr.cc/virtual/2022/poster/6657
|
Deep AutoAugment
| null | null | 3 | 4.25 |
Poster
|
5;5;4;3
|
2;3;3;3
|
null | null |
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6992; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Emily Black, Zifan Wang, Matt Fredrikson
|
https://iclr.cc/virtual/2022/poster/6992
|
deep models;deep networks;explainability;counterfactual explanations;consistency;consistent predictions;model duplicity;random initialization
| null | 2.75 | null |
https://openreview.net/forum?id=St6eyiTEHnG
|
iclr
| 0.57735 | 0.816497 | null |
main
| 5.25 |
3;6;6;6
|
2;3;4;3
|
https://iclr.cc/virtual/2022/poster/6992
|
Consistent Counterfactuals for Deep Models
| null | null | 3 | 3.5 |
Poster
|
3;4;4;3
|
2;3;3;3
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;2;3;4
| null | null | null |
Data Augmentation;Neural Network;Coresets
| null | 2.5 | null | null |
iclr
| -0.555556 | 0 | null |
main
| 4.25 |
3;3;5;6
|
3;3;3;3
| null |
Data-Efficient Augmentation for Training Neural Networks
| null | null | 3 | 3.25 |
Reject
|
3;4;3;3
|
3;2;2;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;4;2;3
| null | null | null |
Knowledge Distillation;Label Smoothing;Supervised Learning;Image Classification;Natural Language Understanding
| null | 2.25 | null | null |
iclr
| -0.333333 | 1 | null |
main
| 5.25 |
5;5;5;6
|
3;3;3;4
| null |
Pseudo Knowledge Distillation: Towards Learning Optimal Instance-specific Label Smoothing Regularization
| null | null | 3.25 | 3.25 |
Reject
|
3;4;3;3
|
2;3;2;2
|
null | null |
2022
| 2.4 |
https://iclr.cc/virtual/2022/poster/6574; None
| null | 0 | null | null | null |
2;1;3;3;3
| null |
Tomer Galanti, Andras Gyorgy, Marcus Hutter
|
https://iclr.cc/virtual/2022/poster/6574
| null | null | 2.8 | null |
https://openreview.net/forum?id=SwIp410B6aQ
|
iclr
| -0.25 | -0.408248 | null |
main
| 6.4 |
6;6;6;6;8
|
4;3;3;4;3
|
https://iclr.cc/virtual/2022/poster/6574
|
On the Role of Neural Collapse in Transfer Learning
| null | null | 3.4 | 3.2 |
Poster
|
4;3;3;3;3
|
3;3;2;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
3;2;2;3
| null | null | null |
network compression;network binarization;contrastive learning
| null | 2.25 | null | null |
iclr
| -0.96225 | 0 | null |
main
| 4.25 |
3;3;5;6
|
3;3;3;3
| null |
Contrastive Mutual Information Maximization for Binary Neural Networks
| null | null | 3 | 4.5 |
Reject
|
5;5;4;4
|
2;2;2;3
|
null | null |
2022
| 3.333333 |
https://iclr.cc/virtual/2022/poster/6176; None
| null | 0 | null | null | null |
4;3;3
| null |
Rob Brekelmans, Sicong(Sheldon) Huang, Marzyeh Ghassemi, Greg Ver Steeg, Roger Grosse, Alireza Makhzani
|
https://iclr.cc/virtual/2022/poster/6176
|
mutual information estimation;annealed importance sampling;energy-based models
| null | 3.333333 | null |
https://openreview.net/forum?id=T0B9AoM_bFg
|
iclr
| 0.5 | 0 | null |
main
| 7.333333 |
6;8;8
|
4;4;4
|
https://iclr.cc/virtual/2022/poster/6176
|
Improving Mutual Information Estimation with Annealed and Energy-Based Bounds
| null | null | 4 | 4.333333 |
Poster
|
4;5;4
|
3;3;4
|
null | null |
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6942; None
| null | 0 | null | null | null |
2;4;3;3
| null |
Nikolay Savinov, Junyoung Chung, Mikolaj Binkowski, Erich Elsen, Aaron v den
|
https://iclr.cc/virtual/2022/poster/6942
|
generative models;text generation;denoising autoencoders
| null | 2.75 | null |
https://openreview.net/forum?id=T0GpzBQ1Fg6
|
iclr
| -0.688247 | -0.688247 | null |
main
| 6.25 |
5;6;6;8
|
4;4;3;3
|
https://iclr.cc/virtual/2022/poster/6942
|
Step-unrolled Denoising Autoencoders for Text Generation
| null | null | 3.5 | 3.5 |
Poster
|
4;3;4;3
|
2;3;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
few-shot learning;task-adaptive semantic feature learning;feature concatenation;feature fusion.
| null | 2.25 | null | null |
iclr
| 1 | 0.707107 | null |
main
| 5.5 |
5;5;6;6
|
2;3;4;3
| null |
Few-Shot Classification with Task-Adaptive Semantic Feature Learning
| null | null | 3 | 3.5 |
Reject
|
3;3;4;4
|
2;2;2;3
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
2;3;3
| null | null | null |
Dataset Condensation;Data-efficient Learning;Distribution Matching;Continual Learning;Neural Architecture Search
| null | 2.666667 | null | null |
iclr
| 0.114708 | 0.993399 | null |
main
| 5.333333 |
3;5;8
|
2;3;4
| null |
Dataset Condensation with Distribution Matching
| null | null | 3 | 3.666667 |
Withdraw
|
4;3;4
|
3;2;3
|
null | null |
2022
| 1.6 | null | null | 0 | null | null | null |
1;1;2;2;2
| null | null | null |
online convex optimization;dynamic regret upper bound;normalized exponentiated gradient;adaptive trick
| null | 0 | null | null |
iclr
| -0.25 | 0.408248 | null |
main
| 3.4 |
3;3;3;3;5
|
3;4;4;3;4
| null |
ENHANCE THE DYNAMIC REGRET VIA OPTIMISM
| null | null | 3.6 | 4.2 |
Withdraw
|
4;4;4;5;4
| null |
null | null |
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/5923; None
| null | 0 | null | null | null |
3;3;3;2
| null |
Ifigeneia Apostolopoulou, Ian Char, Elan Rosenfeld, Artur Dubrawski
|
https://iclr.cc/virtual/2022/poster/5923
|
variational inference;approximate inference;deep probabilistic models;deep probabilistic learning;variational autoencoder;probabilistic methods for deep learning;attention
| null | 3.25 | null |
https://openreview.net/forum?id=T4-65DNlDij
|
iclr
| 0.333333 | 0.333333 | null |
main
| 7.5 |
6;8;8;8
|
3;3;3;4
|
https://iclr.cc/virtual/2022/poster/5923
|
Deep Attentive Variational Inference
| null | null | 3.25 | 3.25 |
Poster
|
3;4;3;3
|
3;4;3;3
|
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