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values |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
null |
University of Edinburgh
|
2022
| 2.25 |
https://iclr.cc/virtual/2022/poster/5897; None
| null | 0 | null | null | null |
2;2;3;2
| null |
Lucas Deecke, Timothy Hospedales, Hakan Bilen
|
https://iclr.cc/virtual/2022/poster/5897
|
transfer learning;latent domains;computer vision
| null | 2.75 | null |
https://openreview.net/forum?id=kG0AtPi6JI1
|
iclr
| 0.57735 | 1 | null |
main
| 5.25 |
3;6;6;6
|
2;3;3;3
|
https://iclr.cc/virtual/2022/poster/5897
|
Visual Representation Learning over Latent Domains
| null | null | 2.75 | 2.5 |
Poster
|
2;2;3;3
|
3;3;3;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2
| null | null | null |
variational autoencoder;deep generative models;outlier detection;data repair
| null | 2.333333 | null | null |
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6
|
4;2;4
| null |
Repairing Systematic Outliers by Learning Clean Subspaces in VAEs
| null | null | 3.333333 | 3 |
Reject
|
2;4;3
|
2;2;3
|
null | null |
2022
| 3.25 | null | null | 0 | null | null | null |
2;4;3;4
| null | null | null | null | null | 2.75 | null | null |
iclr
| -0.816497 | 0.57735 | null |
main
| 5.25 |
3;6;6;6
|
3;4;3;4
| null |
On Pseudo-Labeling for Class-Mismatch Semi-Supervised Learning
| null | null | 3.5 | 4 |
Reject
|
5;3;4;4
|
2;3;3;3
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;2;3
| null | null | null |
Model Compression;neural network quantization;sparse principal component analysis;vector quantization
| null | 2 | null | null |
iclr
| -0.904194 | 0.996616 | null |
main
| 4.666667 |
1;5;8
|
2;3;4
| null |
Quantized sparse PCA for neural network weight compression
| null | null | 3 | 3.666667 |
Reject
|
5;3;3
|
1;2;3
|
null |
University of California, Berkeley; Adobe Research
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6376; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Zhuang Liu, Zhiqiu Xu, Hung-Ju Wang, trevor darrell, Evan Shelhamer
|
https://iclr.cc/virtual/2022/poster/6376
|
Efficient Inference;Anytime Inference;Semantic Segmentation;Dense Prediction;Computer Vision
| null | 2.5 | null |
https://openreview.net/forum?id=kNKFOXleuC
|
iclr
| -0.57735 | 0 | null |
main
| 6.5 |
6;6;6;8
|
3;3;3;3
|
https://iclr.cc/virtual/2022/poster/6376
|
Anytime Dense Prediction with Confidence Adaptivity
|
https://github.com/liuzhuang13/anytime
| null | 3 | 3.5 |
Poster
|
3;4;4;3
|
2;2;3;3
|
null | null |
2022
| 1.5 | null | null | 0 | null | null | null |
1;1;2;2
| null | null | null | null | null | 1.75 | null | null |
iclr
| -0.904534 | 0.57735 | null |
main
| 4 |
3;3;5;5
|
3;2;3;3
| null |
L2BGAN: An image enhancement model for image quality improvement and image analysis tasks without paired supervision
| null | null | 2.75 | 3.75 |
Reject
|
4;5;3;3
|
1;1;2;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
unsupervised learning;reinforcement learning;exploration
| null | 3.25 | null | null |
iclr
| 0.366508 | 0.518321 | null |
main
| 6.25 |
3;6;8;8
|
2;4;3;3
| null |
CIC: Contrastive Intrinsic Control for Unsupervised Skill Discovery
| null | null | 3 | 3.5 |
Reject
|
3;4;4;3
|
3;3;4;3
|
null |
1The Swiss AI Lab IDSIA, Universit `a della Svizzera italiana2Politecnico di Milano; The Swiss AI Lab IDSIA, Universit `a della Svizzera italiana
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/5891; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Andrea Cini, Ivan Marisca, Cesare Alippi
|
https://iclr.cc/virtual/2022/poster/5891
|
graph neural networks;missing data;time series analysis;time series imputation
| null | 2.5 | null |
https://openreview.net/forum?id=kOu3-S3wJ7
|
iclr
| 0.707107 | 0 | null |
main
| 7 |
6;6;8;8
|
4;3;3;4
|
https://iclr.cc/virtual/2022/poster/5891
|
Filling the G_ap_s: Multivariate Time Series Imputation by Graph Neural Networks
| null | null | 3.5 | 3 |
Poster
|
2;3;4;3
|
2;3;2;3
|
null |
Tencent AI Lab, UC Los Angeles; Tencent AI Lab, Xiamen University; Tencent AI Lab, Tsinghua University; Tencent AI Lab
|
2022
| 2.8 |
https://iclr.cc/virtual/2022/poster/6718; None
| null | 0 | null | null | null |
3;3;3;2;3
| null |
Jiawei Yang, Hanbo Chen, Jiangpeng Yan, Xiaoyu Chen, Jianhua Yao
|
https://iclr.cc/virtual/2022/poster/6718
|
Few shot learning;Histology Image;Knowledge Transferring
| null | 3 | null |
https://openreview.net/forum?id=kQ2SOflIOVC
|
iclr
| 0.748455 | -0.068041 | null |
main
| 6.6 |
5;6;6;8;8
|
4;3;3;3;4
|
https://iclr.cc/virtual/2022/poster/6718
|
Towards Better Understanding and Better Generalization of Low-shot Classification in Histology Images with Contrastive Learning
|
https://github.com/TencentAILabHealthcare/Few-shot-WSI
| null | 3.4 | 3.6 |
Poster
|
3;3;4;4;4
|
2;3;3;3;4
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;1;2;3
| null | null | null |
graph mining;oversmoothing;contrastive learning
| null | 2 | null | null |
iclr
| -0.555556 | 0.555556 | null |
main
| 4.25 |
3;3;5;6
|
3;2;3;3
| null |
Tackling Oversmoothing of GNNs with Contrastive Learning
| null | null | 2.75 | 4.25 |
Reject
|
4;5;4;4
|
2;1;2;3
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
2;3;3
| null | null | null |
pre-training;fine-tuning;generalization theory
| null | 3.333333 | null | null |
iclr
| -0.755929 | 0.944911 | null |
main
| 4.666667 |
3;5;6
|
2;3;3
| null |
Improved Fine-tuning by Leveraging Pre-training Data: Theory and Practice
| null | null | 2.666667 | 3.666667 |
Withdraw
|
4;4;3
|
3;3;4
|
null |
Helmholtz Centre Hereon; University of Tübingen; TU Munich
|
2022
| 2.25 |
https://iclr.cc/virtual/2022/poster/6518; None
| null | 0 | null | null | null |
2;2;2;3
| null |
Poornima Ramesh, Jan-Matthis Lueckmann, Jan Boelts, Álvaro Tejero-Cantero, David Greenberg, Pedro Goncalves, Jakob Macke
|
https://iclr.cc/virtual/2022/poster/6518
|
Machine Learning;simulation-based inference;generative adversarial networks;approximate bayesian computation;data-driven modelling;GANs;SBI;likelihood-free inference;implicit models
| null | 2.25 | null |
https://openreview.net/forum?id=kR1hC6j48Tp
|
iclr
| 0 | -0.229416 | null |
main
| 6.25 |
5;6;6;8
|
3;4;4;3
|
https://iclr.cc/virtual/2022/poster/6518
|
GATSBI: Generative Adversarial Training for Simulation-Based Inference
| null | null | 3.5 | 4 |
Poster
|
4;3;5;4
|
2;2;2;3
|
null | null |
2022
| 2.4 | null | null | 0 | null | null | null |
2;2;3;2;3
| null | null | null |
MRTA;Reinforcement learning;graph learning
| null | 2.4 | null | null |
iclr
| -0.389249 | 0.800095 | null |
main
| 5.6 |
3;5;6;6;8
|
2;3;3;3;3
| null |
Learning to Solve Multi-Robot Task Allocation with a Covariant-Attention based Neural Architecture
| null | null | 2.8 | 3 |
Reject
|
4;2;3;3;3
|
3;3;3;3;0
|
null |
Rice University; UIUC
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6173; None
| null | 0 | null | null | null |
3;2;3;3
| null |
Cheng Wan, Youjie Li, Cameron Wolfe, Anastasios Kyrillidis, Nam Sung Kim, Yingyan Lin
|
https://iclr.cc/virtual/2022/poster/6173
|
Graph Neural Networks;Graph Convolutional Networks;Distributed Training;Asynchronous Training;Full-Graph Training;Large-Graph Training;Stale Features
| null | 3 | null |
https://openreview.net/forum?id=kSwqMH0zn1F
|
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6;6
|
3;3;4;3
|
https://iclr.cc/virtual/2022/poster/6173
|
PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication
|
https://github.com/RICE-EIC/PipeGCN
| null | 3.25 | 3.5 |
Poster
|
4;4;3;3
|
3;3;3;3
|
null | null |
2022
| 2.2 | null | null | 0 | null | null | null |
1;2;3;2;3
| null | null | null | null | null | 2.4 | null | null |
iclr
| -0.838525 | -0.684653 | null |
main
| 4 |
1;3;5;5;6
|
4;4;3;4;3
| null |
Assessing Deep Reinforcement Learning Policies via Natural Corruptions at the Edge of Imperceptibility
| null | null | 3.6 | 4.2 |
Withdraw
|
5;4;4;4;4
|
2;2;3;2;3
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
2;2;4
| null | null | null |
visual attention model;reinforcement learning
| null | 2.666667 | null | null |
iclr
| -1 | 1 | null |
main
| 4 |
3;3;6
|
3;3;4
| null |
Unifying Top-down and Bottom-up for Recurrent Visual Attention
| null | null | 3.333333 | 3.333333 |
Reject
|
4;4;2
|
2;2;4
|
null |
Paper under double-blind review
|
2022
| 2.25 | null | null | 0 | null | null | null |
1;2;3;3
| null | null | null | null | null | 2.5 | null | null |
iclr
| -0.727607 | 0.70014 | null |
main
| 5.25 |
3;5;5;8
|
3;4;3;4
| null |
Avoiding Robust Misclassifications for Improved Robustness without Accuracy Loss
| null | null | 3.5 | 3.25 |
Reject
|
4;3;3;3
|
2;2;3;3
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;3;3;3
| null | null | null |
Constrained Reinforcement Learning;Pareto optimization;Constrained Markov Decision Process
| null | 3 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
5;5;5;5
|
2;3;3;3
| null |
Rethinking Pareto Approaches in Constrained Reinforcement Learning
| null | null | 2.75 | 3.25 |
Withdraw
|
4;3;3;3
|
3;3;3;3
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;3;2
| null | null | null |
data augmentation;regression;mixup;reinforcement learning
| null | 2.333333 | null | null |
iclr
| -0.5 | 1 | null |
main
| 4.333333 |
3;5;5
|
2;3;3
| null |
MixRL: Data Mixing Augmentation for Regression using Reinforcement Learning
| null | null | 2.666667 | 3.666667 |
Reject
|
4;3;4
|
2;3;2
|
null |
University of Tübingen
|
2022
| 2.25 |
https://iclr.cc/virtual/2022/poster/6748; None
| null | 0 | null | null | null |
2;2;2;3
| null |
Manuel Glöckler, Michael Deistler, Jakob Macke
|
https://iclr.cc/virtual/2022/poster/6748
|
likelihood-free inference;simulation-based inference;variational inference;neural density estimation
| null | 2.75 | null |
https://openreview.net/forum?id=kZ0UYdhqkNY
|
iclr
| 0 | -0.57735 | null |
main
| 7 |
6;6;8;8
|
4;4;4;3
|
https://iclr.cc/virtual/2022/poster/6748
|
Variational methods for simulation-based inference
| null | null | 3.75 | 3.5 |
Spotlight
|
4;3;4;3
|
2;3;3;3
|
null |
Paper under double-blind review
|
2022
| 0 | null | null | 0 | null | null | null | null | null | null | null | null | null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 0 | null | null | null |
Quantum Alphatron
| null | null | 0 | 0 |
Desk Reject
| null | null |
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
fairness;statistical learning;PAC;social welfare
| null | 2 | null | null |
iclr
| -1 | 0.522233 | null |
main
| 3.5 |
3;3;3;5
|
3;4;2;4
| null |
On Learning with Fairness Trade-Offs
| null | null | 3.25 | 3.5 |
Reject
|
4;4;4;2
|
2;2;2;2
|
null |
Argonne National Laboratory & University of Chicago; Pacifiic Northwest National Laboratory & National Virtual Biotechnology Laboratory, US Department of Energy; University of Tennessee, Knoxville & Oak Ridge National Laboratory & National Virtual Biotechnology Laboratory, US Department of Energy; Argonne National Laboratory & National Virtual Biotechnology Laboratory, US Department of Energy; University of California, Berkeley & National Virtual Biotechnology Laboratory, US Department of Energy; Lawrence Berkeley National Laboratory & National Virtual Biotechnology Laboratory, US Department of Energy; University of Chicago; Oak Ridge National Laboratory & National Virtual Biotechnology Laboratory, US Department of Energy
|
2022
| 2.666667 |
https://iclr.cc/virtual/2022/poster/6351; None
| null | 0 | null | null | null |
2;3;3
| null |
Yulun Wu, Nicholas Choma, Andrew Chen, Mikaela Cashman, Erica Teixeira Prates, Veronica Melesse Vergara, Manesh Shah, Austin Clyde, Thomas Brettin, Wibe de Jong, Neeraj Kumar, Martha Head, Rick Stevens, Peter Nugent, Daniel Jacobson, James Brown
|
https://iclr.cc/virtual/2022/poster/6351
|
reinforcement learning;graph neural network;molecule generation;drug discovery;curiosity-driven policy
| null | 1.666667 | null |
https://openreview.net/forum?id=kavTY__jxp
|
iclr
| 0.5 | -0.5 | null |
main
| 6.666667 |
6;6;8
|
4;3;3
|
https://iclr.cc/virtual/2022/poster/6351
|
Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery
| null | null | 3.333333 | 3.666667 |
Poster
|
3;4;4
|
2;0;3
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
2;3;3
| null | null | null | null | null | 3.333333 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
3;6;6
|
3;3;3
| null |
Why be adversarial? Let's cooperate!: Cooperative Dataset Alignment via JSD Upper Bound
| null | null | 3 | 4 |
Reject
|
4;4;4
|
4;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
Molecular Conformation Generation
| null | 1.75 | null | null |
iclr
| 0.408248 | 0.288675 | null |
main
| 5 |
3;5;6;6
|
3;2;4;3
| null |
Direct Molecular Conformation Generation
|
https://github.com/DirectMolecularConfGen/DMCG
| null | 3 | 4 |
Reject
|
3;5;3;5
|
2;0;2;3
|
null |
AWS AI Labs; Massachusetts Institute of Technology; Rutgers University
|
2022
| 2.666667 |
https://iclr.cc/virtual/2022/poster/7145; None
| null | 0 | null | null | null |
3;3;2
| null |
Zihao Xu, Hao He, Guang-He Lee, Bernie Wang, Hao Wang
|
https://iclr.cc/virtual/2022/poster/7145
|
Graphs;Network Topology;Transfer Learning;Domain Adaptation;Adversarial Learning
| null | 1.666667 | null |
https://openreview.net/forum?id=kcwyXtt7yDJ
|
iclr
| -0.866025 | 0 | null |
main
| 5.666667 |
5;6;6
|
3;3;3
|
https://iclr.cc/virtual/2022/poster/7145
|
Graph-Relational Domain Adaptation
|
https://github.com/Wang-ML-Lab/GRDA
| null | 3 | 4 |
Poster
|
5;3;4
|
2;3;0
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
Differential Privacy;Certified Robustness;Pre-trained Classifiers;Input Perturbation
| null | 2.25 | null | null |
iclr
| -0.333333 | 0.870388 | null |
main
| 4.25 |
3;3;5;6
|
2;3;4;4
| null |
Two Birds, One Stone: Achieving both Differential Privacy and Certified Robustness for Pre-trained Classifiers via Input Perturbation
| null | null | 3.25 | 3.75 |
Reject
|
4;4;3;4
|
2;2;2;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
Sparse Modeling;Image Generation
| null | 2.5 | null | null |
iclr
| -0.555556 | 0.555556 | null |
main
| 4.25 |
3;3;5;6
|
2;3;3;3
| null |
Improved Image Generation via Sparsity
| null | null | 2.75 | 3.25 |
Reject
|
3;4;3;3
|
2;2;3;3
|
null |
ASRI, Department of ECE, Seoul National University, Seoul, Korea; NVIDIA; ASRI, Department of ECE, Seoul National University, Seoul, Korea
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6155; None
| null | 0 | null | null | null |
3;3;3
| null |
Seungjun Nah, Sanghyun Son, Jaerin Lee, Kyoung Mu Lee
|
https://iclr.cc/virtual/2022/poster/6155
|
Deblur;Reblur;Loss;Test-time adaptation;Self-supervised
| null | 2 | null |
https://openreview.net/forum?id=kezNJydWvE
|
iclr
| 0 | 0.981981 | null |
main
| 6.333333 |
5;6;8
|
2;3;4
|
https://iclr.cc/virtual/2022/poster/6155
|
Clean Images are Hard to Reblur: Exploiting the Ill-Posed Inverse Task for Dynamic Scene Deblurring
| null | null | 3 | 4 |
Poster
|
4;4;4
|
0;3;3
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
3;2;2
| null | null | null |
Imitation Learning;Generative Models;Multi-Agent;Time-Series Prediction
| null | 2 | null | null |
iclr
| 0 | 0 | null |
main
| 3 |
3;3;3
|
2;2;2
| null |
SS-MAIL: Self-Supervised Multi-Agent Imitation Learning
| null | null | 2 | 3 |
Withdraw
|
3;4;2
|
2;2;2
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
recommender systems;preference shift;preference estimation;preference tampering
| null | 2 | null | null |
iclr
| -0.57735 | 0.816497 | null |
main
| 5.75 |
5;6;6;6
|
2;4;3;3
| null |
Estimating and Penalizing Induced Preference Shifts in Recommender Systems
| null | null | 3 | 3.5 |
Reject
|
4;3;3;4
|
2;3;3;0
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;1;2;3
| null | null | null |
momentum;variance reduction
| null | 1.2 | null | null |
iclr
| 0.534522 | 0.918559 | null |
main
| 2.6 |
1;3;3;3;3
|
1;3;3;3;4
| null |
Momentum as Variance-Reduced Stochastic Gradient
| null | null | 2.8 | 3.8 |
Withdraw
|
3;4;5;3;4
|
1;2;1;1;1
|
null |
School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ 85281, USA; Cognitive Computing Lab, Baidu Research, Bellevue, WA 98004, USA
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6248; None
| null | 0 | null | null | null |
2;3;3;4
| null |
Yingzhen Yang, Ping Li
|
https://iclr.cc/virtual/2022/poster/6248
|
Discriminative Similarity;Rademacher Complexity;Generalization Bound;Data Clustering
| null | 3 | null |
https://openreview.net/forum?id=kj0_45Y4r9i
|
iclr
| 0.899229 | 0.760886 | null |
main
| 6.25 |
5;6;6;8
|
2;3;4;4
|
https://iclr.cc/virtual/2022/poster/6248
|
Discriminative Similarity for Data Clustering
| null | null | 3.25 | 3.75 |
Poster
|
3;3;4;5
|
2;3;3;4
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;3;2
| null | null | null | null | null | 1.25 | null | null |
iclr
| 0.57735 | 0 | null |
main
| 4.5 |
3;5;5;5
|
3;3;3;3
| null |
FaceDet3D: Facial Expressions with 3D Geometric Detail Hallucination
| null | null | 3 | 3.5 |
Reject
|
3;3;4;4
|
2;0;1;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;3;2
| null | null | null |
Secure Dataset Release;Data Poisoning;Availability Attack
| null | 2.5 | null | null |
iclr
| 0.555556 | 0.555556 | null |
main
| 4.25 |
3;3;5;6
|
2;3;3;3
| null |
Protecting Proprietary Data: Poisoning for Secure Dataset Release
| null | null | 2.75 | 3.75 |
Withdraw
|
3;4;4;4
|
2;3;2;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
Learning distribution;ReLU;Truncated Gaussian;Unsupervised learning
| null | 0.25 | null | null |
iclr
| -0.333333 | -0.57735 | null |
main
| 3.5 |
3;3;3;5
|
3;4;4;3
| null |
LEARNING DISTRIBUTIONS GENERATED BY SINGLE-LAYER RELU NETWORKS IN THE PRESENCE OF ARBITRARY OUTLIERS
| null | null | 3.5 | 3.25 |
Reject
|
3;3;4;3
|
0;1;0;0
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
Feature Learning;Shapley Value;Click-through Rate;Asset Pricing
| null | 2.25 | null | null |
iclr
| -0.406181 | -0.816497 | null |
main
| 4.25 |
3;3;5;6
|
4;3;3;2
| null |
Feature Shapley: A general framework to discovering useful feature interactions
| null | null | 3 | 3.75 |
Withdraw
|
5;3;4;3
|
2;2;2;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
contrastive learning;representation learning;image classification;mutual information
| null | 3 | null | null |
iclr
| 0 | 0.57735 | null |
main
| 5.5 |
5;5;6;6
|
2;3;3;3
| null |
Self-Contrastive Learning
| null | null | 2.75 | 4 |
Reject
|
4;4;4;4
|
3;2;4;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;1;3;2
| null | null | null | null | null | 1.25 | null | null |
iclr
| -0.707107 | -0.57735 | null |
main
| 4 |
3;3;5;5
|
3;3;3;2
| null |
Robust Graph Data Learning with Latent Graph Convolutional Representation
| null | null | 2.75 | 4 |
Withdraw
|
4;5;4;3
|
2;1;0;2
|
null |
Paper under double-blind review
|
2022
| 2.25 | null | null | 0 | null | null | null |
2;1;3;3
| null | null | null |
Clustering;Electronic Health Records
| null | 2.25 | null | null |
iclr
| 0 | 0 | null |
main
| 6 |
5;5;6;8
|
3;3;3;3
| null |
Cluster-based Feature Importance Learning for Electronic Health Record Time-series
| null | null | 3 | 3.75 |
Reject
|
3;5;3;4
|
2;2;3;2
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;2;3
| null | null | null |
Representation Learning;Reinforcement Learning;Active Learning
| null | 2.333333 | null | null |
iclr
| 0.5 | 1 | null |
main
| 5.666667 |
5;6;6
|
2;3;3
| null |
Reinforcement Learning with Efficient Active Feature Acquisition
| null | null | 2.666667 | 3.333333 |
Reject
|
3;3;4
|
2;2;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
1;3;2;3
| null | null | null |
Non-linear assignment;Deep Learning;Stable Matching;3D Point Cloud Matching
| null | 2.5 | null | null |
iclr
| 0.408248 | 0.866025 | null |
main
| 5 |
3;5;6;6
|
2;3;4;3
| null |
WeaveNet: A Differentiable Solver for Non-linear Assignment Problems
| null | null | 3 | 3.5 |
Withdraw
|
3;4;3;4
|
1;3;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
Information-Aware Time Series Meta-Contrastive Learning
| null | 2.75 | null | null |
iclr
| -0.5547 | 0.9461 | null |
main
| 6 |
3;5;6;10
|
2;2;3;4
| null |
Information-Aware Time Series Meta-Contrastive Learning
| null | null | 2.75 | 4 |
Reject
|
4;4;5;3
|
1;3;4;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;3;2
| null | null | null |
General Robustness;Data Valuation;Data Utility Learning
| null | 2 | null | null |
iclr
| 0.57735 | 0.57735 | null |
main
| 5.5 |
5;5;6;6
|
3;2;3;3
| null |
Towards General Robustness to Bad Training Data
| null | null | 2.75 | 3.25 |
Reject
|
3;3;3;4
|
2;2;2;2
|
null |
University of Cambridge; Carnegie Mellon University
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6265; None
| null | 0 | null | null | null |
3;3;3
| null |
Yandong Wen, Weiyang Liu, Adrian Weller, Bhiksha Raj, Rita Singh
|
https://iclr.cc/virtual/2022/poster/6265
| null | null | 3.333333 | null |
https://openreview.net/forum?id=l3SDgUh7qZO
|
iclr
| 0 | 0 | null |
main
| 8 |
8;8;8
|
3;4;3
|
https://iclr.cc/virtual/2022/poster/6265
|
SphereFace2: Binary Classification is All You Need for Deep Face Recognition
|
https://github.com/OpenSphere
| null | 3.333333 | 4 |
Spotlight
|
3;4;5
|
4;3;3
|
null | null |
2022
| 2.4 | null | null | 0 | null | null | null |
3;2;2;2;3
| null | null | null |
regularizer;maximum entropy;uncertainty estimation;data-shift robustness;calibration;out-of-distribution detection
| null | 2.6 | null | null |
iclr
| -0.731925 | 0 | null |
main
| 5 |
3;5;5;6;6
|
3;4;2;3;3
| null |
Mix-MaxEnt: Creating High Entropy Barriers To Improve Accuracy and Uncertainty Estimates of Deterministic Neural Networks
| null | null | 3 | 3.8 |
Reject
|
5;3;4;4;3
|
3;3;2;2;3
|
null |
MIT CSAIL; MIT-IBM Watson AI Lab
|
2022
| 3.5 |
https://iclr.cc/virtual/2022/poster/7011; None
| null | 0 | null | null | null |
4;3;3;4
| null |
Minghao Guo, Veronika Thost, Beichen Li, Payel Das, Jie Chen, Wojciech Matusik
|
https://iclr.cc/virtual/2022/poster/7011
|
molecular generation;graph grammar;data efficient generative model
| null | 3.25 | null |
https://openreview.net/forum?id=l4IHywGq6a
|
iclr
| 0 | 0 | null |
main
| 8 |
8;8;8;8
|
4;4;4;3
|
https://iclr.cc/virtual/2022/poster/7011
|
Data-Efficient Graph Grammar Learning for Molecular Generation
|
https://github.com/gmh14/data_efficient_grammar
| null | 3.75 | 3.5 |
Oral
|
4;3;4;3
|
3;3;4;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
1;2;3
| null | null | null |
private neural network inference;privacy;security;performance
| null | 1.333333 | null | null |
iclr
| -0.802955 | 0.802955 | null |
main
| 3.333333 |
1;3;6
|
1;3;3
| null |
Tabula: Efficiently Computing Nonlinear Activation Functions for Private Neural Network Inference
| null | null | 2.333333 | 3 |
Withdraw
|
5;2;2
|
1;3;0
|
null |
University of Florida
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/5930; None
| null | 0 | null | null | null |
2;3;2;3
| null |
Hadi Abdullah, Aditya Karlekar, Vincent Bindschaedler, Patrick Traynor
|
https://iclr.cc/virtual/2022/poster/5930
|
optimization attacks;transferability;adversarial machine learning
| null | 2.75 | null |
https://openreview.net/forum?id=l5aSHXi8jG5
|
iclr
| -0.57735 | 0.333333 | null |
main
| 5.75 |
5;5;5;8
|
3;3;2;3
|
https://iclr.cc/virtual/2022/poster/5930
|
Demystifying Limited Adversarial Transferability in Automatic Speech Recognition Systems
| null | null | 2.75 | 3.5 |
Poster
|
4;3;4;3
|
2;3;3;3
|
null |
The University of Edinburgh, UK; DataCanvas Lab, DataCanvas, Beijing, China
|
2022
| 3.5 |
https://iclr.cc/virtual/2022/poster/7019; None
| null | 0 | null | null | null |
3;4;3;4
| null |
Bochen Lyu, Zhanxing Zhu
|
https://iclr.cc/virtual/2022/poster/7019
|
adversarial training;adversarial examples
| null | 2 | null |
https://openreview.net/forum?id=l8It-0lE5e7
|
iclr
| -0.57735 | 0.904534 | null |
main
| 6.5 |
5;5;8;8
|
3;2;4;4
|
https://iclr.cc/virtual/2022/poster/7019
|
Implicit Bias of Adversarial Training for Deep Neural Networks
| null | null | 3.25 | 3.25 |
Poster
|
3;4;3;3
|
0;4;4;0
|
null | null |
2022
| 1 | null | null | 0 | null | null | null |
1;1;1
| null | null | null | null | null | 1 | null | null |
iclr
| 0 | -1 | null |
main
| 2.333333 |
1;3;3
|
3;2;2
| null |
LMSA: Low-relation Mutil-head Self-Attention Mechanism in Visual Transformer
| null | null | 2.333333 | 5 |
Reject
|
5;5;5
|
1;1;1
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
Continual learning;Class incremental learning;Stability-plasticity dilemma;Sparse neural networks;Knowledge-Awareness
| null | 2.25 | null | null |
iclr
| -0.301511 | 0.707107 | null |
main
| 4.5 |
3;3;6;6
|
3;2;4;3
| null |
Addressing the Stability-Plasticity Dilemma via Knowledge-Aware Continual Learning
| null | null | 3 | 4.25 |
Reject
|
4;5;5;3
|
2;2;2;3
|
null |
Under double-blind review
|
2022
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Robustness;Fast Adversarial Training;Catastrophic Overfitting
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 0 | null | null | null |
Towards Understanding Catastrophic Overfitting in Fast Adversarial Training
| null | null | 0 | 0 |
Desk Reject
| null | null |
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;2;3
| null | null | null |
Financial market forecasting;Deep fusion;Collaborative attention
| null | 2 | null | null |
iclr
| -0.866025 | 1 | null |
main
| 4.333333 |
3;5;5
|
2;3;3
| null |
A Collaborative Attention Adaptive Network for Financial Market Forecasting
| null | null | 2.666667 | 4 |
Reject
|
5;4;3
|
2;2;2
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
Contrastive learning;Data-efficient learning;Hard sample generation
| null | 2.5 | null | null |
iclr
| 0 | 0.132453 | null |
main
| 4.75 |
3;5;5;6
|
3;3;4;3
| null |
Data-Efficient Contrastive Learning by Differentiable Hard Sample and Hard Positive Pair Generation
| null | null | 3.25 | 4 |
Withdraw
|
4;4;4;4
|
2;2;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2
| null | null | null |
neural decoding;visual stimulus image reconstruction;visual attention;encoder-decoder;fMRI
| null | 2 | null | null |
iclr
| 0.5 | -1 | null |
main
| 3.666667 |
3;3;5
|
3;3;2
| null |
Foreground-attention in neural decoding: Guiding Loop-Enc-Dec to reconstruct visual stimulus images from fMRI
| null | null | 2.666667 | 4.333333 |
Reject
|
5;3;5
|
2;1;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
3;2;2;2
| null | null | null |
Backdoor Sanitation;Deep Neural Network Security;Feature Grinding
| null | 1.75 | null | null |
iclr
| 0.333333 | 0 | null |
main
| 3.5 |
3;3;3;5
|
2;2;2;2
| null |
Feature Grinding: Efficient Backdoor Sanitation in Deep Neural Networks
| null | null | 2 | 3.75 |
Withdraw
|
4;4;3;4
|
2;1;2;2
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
3;2;3
| null | null | null |
Curriculum Learning;Reinforcement Learning;Self-Paced Learning
| null | 2.333333 | null | null |
iclr
| 0 | 0.5 | null |
main
| 5.666667 |
5;6;6
|
3;3;4
| null |
Metrics Matter: A Closer Look on Self-Paced Reinforcement Learning
| null | null | 3.333333 | 3 |
Reject
|
3;4;2
|
2;2;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
3;3;2;2
| null | null | null | null | null | 2 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
5;5;5;5
|
3;3;3;3
| null |
Heterologous Normalization
| null | null | 3 | 4 |
Reject
|
4;4;4;4
|
2;2;2;2
|
null |
Nvidia; Google Research
|
2022
| 2.666667 |
https://iclr.cc/virtual/2022/poster/6372; None
| null | 0 | null | null | null |
3;2;3
| null |
Xiuye Gu, Tsung-Yi Lin, Weicheng Kuo, Yin Cui
|
https://iclr.cc/virtual/2022/poster/6372
|
Open-vocabulary recognition;Object detection;Knowledge distillation
| null | 3.666667 | null |
https://openreview.net/forum?id=lL3lnMbR4WU
|
iclr
| -0.5 | 0.5 | null |
main
| 7.333333 |
6;8;8
|
3;4;3
|
https://iclr.cc/virtual/2022/poster/6372
|
Open-vocabulary Object Detection via Vision and Language Knowledge Distillation
|
https://github.com/tensorflow/tpu/tree/master/models/official/detection/projects/vild
| null | 3.333333 | 4.666667 |
Poster
|
5;5;4
|
3;4;4
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;3;1;2
| null | null | null |
Model Learning;Model Based Reinforcement Learning;Control
| null | 2.5 | null | null |
iclr
| 0.408248 | 0.288675 |
https://sites.google.com/view/learning-better-models
|
main
| 5 |
3;5;6;6
|
3;2;4;3
| null |
Learning Dynamics Models for Model Predictive Agents
| null | null | 3 | 3.5 |
Reject
|
3;4;4;3
|
1;3;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2;2
| null | null | null |
Pre-trained Language Models;Masked Language Modeling;False Negatives;Natural Language Understanding
| null | 2.2 | null | null |
iclr
| -0.408248 | 1 | null |
main
| 4.2 |
3;3;5;5;5
|
2;2;3;3;3
| null |
Language Model Pre-training on True Negatives
| null | null | 2.6 | 3.8 |
Reject
|
4;4;4;3;4
|
2;2;2;3;2
|
null |
EPFL; EPFL, UC Berkeley
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6644; None
| null | 0 | null | null | null |
2;4;3;3
| null |
Andrei Afonin, Sai Karimireddy
|
https://iclr.cc/virtual/2022/poster/6644
|
Federated Learning;Knowledge Distillation;Model Agnostic Communication;Kernel Regression
| null | 2.75 | null |
https://openreview.net/forum?id=lQI_mZjvBxj
|
iclr
| -0.140028 | 0.70014 | null |
main
| 5.75 |
3;6;6;8
|
3;4;3;4
|
https://iclr.cc/virtual/2022/poster/6644
|
Towards Model Agnostic Federated Learning Using Knowledge Distillation
| null | null | 3.5 | 3.5 |
Poster
|
4;3;3;4
|
2;4;2;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
1;2;2;3
| null | null | null | null | null | 2.5 | null | null |
iclr
| -0.777778 | 0.96225 | null |
main
| 4.25 |
3;3;5;6
|
2;2;3;3
| null |
Efficient Ensembles of Graph Neural Networks
| null | null | 2.5 | 3.75 |
Withdraw
|
4;4;4;3
|
2;2;2;4
|
null |
Department of Mathematics and Computer Science, University of Basel; MPI for Intelligent Systems, Tübingen, Germany; ETH Zürich, Switzerland; ETH Zürich, Switzerland; MPI for Intelligent Systems, Tübingen, Germany
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6861; None
| null | 0 | null | null | null |
1;3;4;4;3
| null |
Sidak Pal Singh, Aurelien Lucchi, Thomas Hofmann, Bernhard Schoelkopf
|
https://iclr.cc/virtual/2022/poster/6861
|
double descent;generalization;neural networks;hessian;flatness
| null | 2.6 | null |
https://openreview.net/forum?id=lTqGXfn9Tv
|
iclr
| 1 | 0.790569 | null |
main
| 7 |
3;8;8;8;8
|
2;3;3;3;4
|
https://iclr.cc/virtual/2022/poster/6861
|
Phenomenology of Double Descent in Finite-Width Neural Networks
|
Available on GitHub (link not provided in text)
| null | 3 | 3.8 |
Poster
|
3;4;4;4;4
|
2;3;2;3;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;3;2
| null | null | null |
network embedding;heterogeneous network embedding;hyperbolic space
| null | 2 | null | null |
iclr
| 0 | 0.57735 | null |
main
| 4 |
3;3;5;5
|
2;3;3;3
| null |
Multi-Vector Embedding on Networks with Taxonomies
| null | null | 2.75 | 4 |
Withdraw
|
4;4;5;3
|
2;2;2;2
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
Contextualized Word Embeddings;Isotropy;Natural Language Processing
| null | 2.5 | null | null |
iclr
| 0.927173 | 0.688247 | null |
main
| 4.75 |
3;5;5;6
|
2;2;3;3
| null |
IsoScore: Measuring the Uniformity of Vector Space Utilization
| null | null | 2.5 | 3.75 |
Withdraw
|
3;4;4;4
|
2;3;3;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
1;2;2;4
| null | null | null | null | null | 2 | null | null |
iclr
| -0.5 | 0.710669 | null |
main
| 5 |
3;3;6;8
|
2;2;4;3
| null |
Generating Transferable Adversarial Patch by Simultaneously Optimizing its Position and Perturbations
| null | null | 2.75 | 4 |
Withdraw
|
5;4;3;4
|
2;0;2;4
|
null |
Carnegie Mellon University
|
2022
| 2.666667 |
https://iclr.cc/virtual/2022/poster/6150; None
| null | 0 | null | null | null |
2;3;3
| null |
Tianqin Li, Zijie Li, Andrew Luo, Harold Rockwell, Amir Barati Farimani, Tai Lee
|
https://iclr.cc/virtual/2022/poster/6150
|
neuroscience;deep learning
| null | 2.666667 | null |
https://openreview.net/forum?id=lY0-7bj0Vfz
|
iclr
| -0.5 | 1 | null |
main
| 6 |
5;5;8
|
3;3;4
|
https://iclr.cc/virtual/2022/poster/6150
|
Prototype memory and attention mechanisms for few shot image generation
| null | null | 3.333333 | 3.333333 |
Poster
|
4;3;3
|
3;2;3
|
null |
Department of Computer Science, ETH Zurich, Switzerland
|
2022
| 2.6 |
https://iclr.cc/virtual/2022/poster/6097; None
| null | 0 | null | null | null |
2;3;2;3;3
| null |
Claudio Ferrari, Mark N Müller, Nikola Jovanović, Martin Vechev
|
https://iclr.cc/virtual/2022/poster/6097
|
Certified Robustness;Branch-and-Bound;Convex Relaxation
| null | 2.2 | null |
https://openreview.net/forum?id=l_amHf1oaK
|
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6;6;6
|
4;2;4;4;2
|
https://iclr.cc/virtual/2022/poster/6097
|
Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound
| null | null | 3.2 | 4 |
Poster
|
5;4;4;3;4
|
0;3;2;3;3
|
null |
Stanford University; Tsinghua University, Stanford University; Tsinghua University
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/6713; None
| null | 0 | null | null | null |
2;2;3;3
| null |
Chuanyu Pan, Yanchao Yang, Kaichun Mo, Yueqi Duan, Leonidas Guibas
|
https://iclr.cc/virtual/2022/poster/6713
|
object-centric;continual learning;representation learning;hypernetwork
| null | 2.5 | null |
https://openreview.net/forum?id=lbauk6wK2-y
|
iclr
| -0.57735 | 0.57735 | null |
main
| 5.5 |
5;5;6;6
|
2;3;3;3
|
https://iclr.cc/virtual/2022/poster/6713
|
Object Pursuit: Building a Space of Objects via Discriminative Weight Generation
|
https://github.com/pptrick/Object-Pursuit
| null | 2.75 | 2.75 |
Poster
|
3;3;2;3
|
2;3;2;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
personalized ranking;class-imbalance;negative sampling;deep learning
| null | 2.25 | null | null |
iclr
| -0.5 | 0.426401 | null |
main
| 5 |
3;3;6;8
|
2;4;3;4
| null |
A Simple and Debiased Sampling Method for Personalized Ranking
| null | null | 3.25 | 4 |
Reject
|
5;4;3;4
|
2;1;3;3
|
null | null |
2022
| 2.8 | null | null | 0 | null | null | null |
2;3;3;2;4
| null | null | null |
Deep learning theory;non-convex optimization
| null | 2.6 | null | null |
iclr
| -0.612372 | 0.228218 | null |
main
| 4.8 |
3;5;5;5;6
|
3;2;2;4;4
| null |
Towards understanding how momentum improves generalization in deep learning
| null | null | 3 | 3.6 |
Reject
|
4;4;4;4;2
|
2;3;2;2;4
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
3;2;3
| null | null | null |
Simultaneous Translation;Monotonic Attention;Speech Translation
| null | 2 | null | null |
iclr
| 0 | 1 | null |
main
| 4 |
3;3;6
|
2;2;4
| null |
Infusing Future Information into Monotonic Attention Through Language Models
| null | null | 2.666667 | 4 |
Withdraw
|
3;5;4
|
2;2;2
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;3;3;3
| null | null | null |
Unsupervised learning;self-supervised learning;few-shot learning;visual representation learning;visual category learning
| null | 2.75 | null | null |
iclr
| 0.333333 | -0.816497 | null |
main
| 5.25 |
3;6;6;6
|
4;2;3;3
| null |
Online Unsupervised Learning of Visual Representations and Categories
| null | null | 3 | 3.25 |
Reject
|
3;3;3;4
|
3;3;2;3
|
null | null |
2022
| 2.6 | null | null | 0 | null | null | null |
4;2;2;2;3
| null | null | null |
Continual Learning;Supervised Learning;Classification;Lifelong Learning;Catastrophic Forgetting;Domain Adaptation;Continual Domain Adaptation
| null | 2.4 | null | null |
iclr
| -0.645497 | 0.395285 | null |
main
| 4 |
3;3;3;5;6
|
2;3;3;3;3
| null |
Center Loss Regularization for Continual Learning
| null | null | 2.8 | 4.4 |
Withdraw
|
5;5;4;4;4
|
3;2;2;2;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
Offline Reinforcement Learning;Batch Reinforcement Learning
| null | 2 | null | null |
iclr
| -0.894427 | 0.707107 | null |
main
| 4 |
3;3;5;5
|
2;3;4;3
| null |
Density Estimation for Conservative Q-Learning
| null | null | 3 | 3.5 |
Reject
|
5;4;2;3
|
2;2;2;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2
| null | null | null | null | null | 2.333333 | null | null |
iclr
| 0 | 0 | null |
main
| 3.666667 |
3;3;5
|
3;3;3
| null |
PGD-2 can be better than FGSM + GradAlign
| null | null | 3 | 4 |
Withdraw
|
4;4;4
|
2;2;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
inductive bias;combinatorial generalization;cognitive psychology;robustness to spurious correlation
| null | 2.5 | null | null |
iclr
| -0.157135 | 0.96225 | null |
main
| 4.25 |
3;3;5;6
|
2;2;3;3
| null |
Distinguishing rule- and exemplar-based generalization in learning systems
| null | null | 2.5 | 3 |
Reject
|
4;3;1;4
|
2;2;2;4
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
3;1;3;2
| null | null | null |
representation learning;understanding deep learning;topological data analysis
| null | 2.5 | null | null |
iclr
| -0.894427 | 0.904534 | null |
main
| 4 |
3;3;5;5
|
2;2;3;4
| null |
Representation Topology Divergence: A Method for Comparing Neural Network Representations.
| null | null | 2.75 | 3.5 |
Withdraw
|
4;5;3;2
|
3;2;2;3
|
null |
Middle East Technical University, Department of Computer Engineering, Ankara, Turkey
|
2022
| 2.4 |
https://iclr.cc/virtual/2022/poster/6138; None
| null | 0 | null | null | null |
2;2;3;3;2
| null |
Samet Cetin, Orhun Baran, Ramazan Gokberk Cinbis
|
https://iclr.cc/virtual/2022/poster/6138
|
zero-shot learning;generative zero-shot learning;generative models
| null | 2 | null |
https://openreview.net/forum?id=ljxWpdBl4V
|
iclr
| 0.080064 | -0.612372 | null |
main
| 5.6 |
5;5;6;6;6
|
3;4;3;3;3
|
https://iclr.cc/virtual/2022/poster/6138
|
Closed-form Sample Probing for Learning Generative Models in Zero-shot Learning
| null | null | 3.2 | 3.6 |
Poster
|
2;5;4;3;4
|
2;2;2;2;2
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;2;4
| null | null | null |
Audio-Visual Learning;Acoustic
| null | 2.5 | null | null |
iclr
| 0 | -0.544331 |
https://sites.google.com/view/nafs-iclr-2022/
|
main
| 4.25 |
3;3;5;6
|
3;4;2;3
| null |
Learning Neural Acoustic Fields
| null | null | 3 | 4 |
Reject
|
4;4;4;4
|
2;3;2;3
|
null |
The Hebrew University of Jerusalem
|
2022
| 3.2 |
https://iclr.cc/virtual/2022/poster/6999; None
| null | 0 | null | null | null |
3;4;2;3;4
| null |
Yoav Levine, Noam Wies, Daniel Jannai, Dan Navon, Yedid Hoshen, Amnon Shashua
|
https://iclr.cc/virtual/2022/poster/6999
|
Language Modeling;Pretraining;Self-attention;Transformers;Expressivity;Separation Rank;Sentence Embeddings
| null | 2.6 | null |
https://openreview.net/forum?id=lnEaqbTJIRz
|
iclr
| 0 | 0 | null |
main
| 8 |
8;8;8;8;8
|
3;4;3;3;3
|
https://iclr.cc/virtual/2022/poster/6999
|
The Inductive Bias of In-Context Learning: Rethinking Pretraining Example Design
| null | null | 3.2 | 2.8 |
Spotlight
|
3;2;3;3;3
|
3;4;2;2;2
|
null |
University of Illinois at Urbana-Champaign; University of Illinois at Urbana-Champaign and HeliXon Limited; Shanghai Jiao Tong University; BIMSA and AIR, Tsinghua University
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/6587; None
| null | 0 | null | null | null |
2;2;3;3
| null |
Zhizhou Ren, Ruihan Guo, Yuan Zhou, Jian Peng
|
https://iclr.cc/virtual/2022/poster/6587
|
Reinforcement Learning;Long-Term Credit Assignment;Reward Redistribution;Return Decomposition
| null | 2.75 | null |
https://openreview.net/forum?id=lpkGn3k2YdD
|
iclr
| -0.522233 | 0.174078 | null |
main
| 7.25 |
5;8;8;8
|
3;2;4;4
|
https://iclr.cc/virtual/2022/poster/6587
|
Learning Long-Term Reward Redistribution via Randomized Return Decomposition
| null | null | 3.25 | 3.25 |
Spotlight
|
4;3;4;2
|
3;2;3;3
|
null | null |
2022
| 1.75 | null | null | 0 | null | null | null |
1;2;2;2
| null | null | null | null | null | 1.75 | null | null |
iclr
| -0.816497 | 0.57735 | null |
main
| 2.5 |
1;3;3;3
|
3;4;4;3
| null |
Learning Stochastic Representations of Physical Systems
| null | null | 3.5 | 4 |
Withdraw
|
5;4;3;4
|
1;2;2;2
|
null |
Center for Data Science, New York University
|
2022
| 3.5 |
https://iclr.cc/virtual/2022/poster/6387; None
| null | 0 | null | null | null |
4;3;3;4
| null |
Alberto Bietti
|
https://iclr.cc/virtual/2022/poster/6387
|
kernel methods;deep learning theory;convolution;approximation;generalization
| null | 3.5 | null |
https://openreview.net/forum?id=lrocYB-0ST2
|
iclr
| -0.57735 | 1 | null |
main
| 7.5 |
6;8;8;8
|
3;4;4;4
|
https://iclr.cc/virtual/2022/poster/6387
|
Approximation and Learning with Deep Convolutional Models: a Kernel Perspective
| null | null | 3.75 | 3.5 |
Poster
|
4;3;3;4
|
4;3;3;4
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
4;2;2;2
| null | null | null |
diffusion;score;guidance;generative
| null | 2.25 | null | null |
iclr
| 0.57735 | 0 | null |
main
| 5.25 |
5;5;5;6
|
3;3;3;3
| null |
Unconditional Diffusion Guidance
| null | null | 3 | 3.5 |
Reject
|
3;3;4;4
|
2;2;2;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
Graph learning;self supervised learning
| null | 2.5 | null | null |
iclr
| -0.688247 | 0.648886 | null |
main
| 4.75 |
3;5;5;6
|
2;3;4;3
| null |
$m$-mix: Generating hard negatives via multiple samples mixing for contrastive learning
| null | null | 3 | 3.5 |
Withdraw
|
4;4;3;3
|
3;2;3;2
|
null |
The Technion; University of Pennsylvania
|
2022
| 3.75 |
https://iclr.cc/virtual/2022/poster/7203; None
| null | 0 | null | null | null |
3;4;4;4
| null |
Shuxiao Chen, Koby Crammer, Hangfeng He, Dan Roth, Weijie J Su
|
https://iclr.cc/virtual/2022/poster/7203
|
Cross-task learning;Natural language processing;Representation learning
| null | 3.25 | null |
https://openreview.net/forum?id=ltM1RMZntpu
|
iclr
| 0 | 0 | null |
main
| 7.5 |
6;8;8;8
|
3;3;3;3
|
https://iclr.cc/virtual/2022/poster/7203
|
Weighted Training for Cross-Task Learning
|
http://cogcomp.org/page/publication_view/963
| null | 3 | 3 |
Oral
|
3;3;3;3
|
3;3;3;4
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
3;2;1;2
| null | null | null |
transfer learning;pretrained language model
| null | 2.25 | null | null |
iclr
| 0 | 0.973329 | null |
main
| 4.75 |
3;5;5;6
|
2;3;3;4
| null |
Identifying the Limits of Cross-Domain Knowledge Transfer for Pretrained Models
| null | null | 3 | 4 |
Reject
|
4;3;5;4
|
3;2;1;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null | null | null | 1.75 | null | null |
iclr
| 0 | 0 | null |
main
| 3 |
3;3;3;3
|
3;2;3;3
| null |
Guiding Transformers to Process in Steps
| null | null | 2.75 | 4 |
Reject
|
5;3;4;4
|
2;2;2;1
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
Few-shot learning;distribution estimation;sampling method
| null | 2.25 | null | null |
iclr
| -0.904534 | 0.57735 | null |
main
| 5.5 |
5;5;6;6
|
2;3;3;3
| null |
Generalized Sampling Method for Few Shot Learning
| null | null | 2.75 | 4.25 |
Withdraw
|
5;5;3;4
|
2;2;2;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;3;2
| null | null | null |
Federated Learning;Optimization;Split Learning;Cross-Silo Learning;Compression;Quantization;Sparsification
| null | 1.5 | null | null |
iclr
| -0.333333 | 0.870388 | null |
main
| 5.25 |
5;5;5;6
|
2;3;2;4
| null |
Compressed-VFL: Communication-Efficient Learning with Vertically Partitioned Data
| null | null | 2.75 | 3.5 |
Reject
|
5;3;3;3
|
0;2;2;2
|
null |
Everdoubling LLC., Seoul, South Korea; Seoul National University
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6082; None
| null | 0 | null | null | null |
3;3;3
| null |
Insu Jeon, Youngjin Park, Gunhee Kim
|
https://iclr.cc/virtual/2022/poster/6082
|
Meta Learning;Few-shot Learning;Bayesian Neural Networks;Variatinoal Dropout
| null | 2.333333 | null |
https://openreview.net/forum?id=lyLVzukXi08
|
iclr
| 1 | -0.5 | null |
main
| 6.666667 |
6;6;8
|
4;3;3
|
https://iclr.cc/virtual/2022/poster/6082
|
Neural Variational Dropout Processes
| null | null | 3.333333 | 3.333333 |
Poster
|
3;3;4
|
2;3;2
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
1;2;3;4
| null | null | null |
deep learning;generalization;neural tangent kernel;kernel regression;inductive bias
| null | 2.25 | null | null |
iclr
| -0.053376 | 0.800641 | null |
main
| 5.5 |
3;5;6;8
|
2;3;3;3
| null |
Neural tangent kernel eigenvalues accurately predict generalization
| null | null | 2.75 | 3.75 |
Reject
|
5;3;2;5
|
2;3;3;1
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;2;4
| null | null | null |
Reinforcement Learning;Representation Learning;Optical Flow Estimation;Structured representation;Self-supervised Learning
| null | 2.5 | null | null |
iclr
| -0.492366 | 0.471405 |
https://sites.google.com/view/iclr2022-s3r
|
main
| 6 |
5;5;6;8
|
4;3;4;4
| null |
Self-Supervised Structured Representations for Deep Reinforcement Learning
| null | null | 3.75 | 2.75 |
Reject
|
2;4;3;2
|
2;3;3;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
adversarial attacks;robustness of neural network;autoencoder;visual cortex;engram cell
| null | 2.5 | null | null |
iclr
| 0 | 0.870388 | null |
main
| 3.5 |
3;3;3;5
|
2;2;3;4
| null |
Denoised Internal Models: a Brain-Inspired Autoencoder against Adversarial Attacks
| null | null | 2.75 | 4 |
Withdraw
|
3;4;5;4
|
2;2;3;3
|
null |
Department of EECS, UC Berkeley; Microsoft Research New England; Department of Computer Science, Harvard University and Department of EECS, MIT
|
2022
| 2.333333 |
https://iclr.cc/virtual/2022/poster/7193; None
| null | 0 | null | null | null |
2;3;2
| null |
Abhishek Shetty, Raaz Dwivedi, Lester Mackey
|
https://iclr.cc/virtual/2022/poster/7193
|
Distribution compression;linear time;thinning;i.i.d. sampling;Markov chain Monte Carlo;maximum mean discrepancy;reproducing kernel Hilbert space
| null | 3.333333 | null |
https://openreview.net/forum?id=lzupY5zjaU9
|
iclr
| 0 | -0.5 | null |
main
| 7.333333 |
6;8;8
|
4;3;4
|
https://iclr.cc/virtual/2022/poster/7193
|
Distribution Compression in Near-Linear Time
| null | null | 3.666667 | 3 |
Poster
|
3;3;3
|
2;4;4
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
3;3;2
| null | null | null |
Algorithmic recourse;Robust optimization
| null | 1.666667 | null | null |
iclr
| -1 | 0.5 | null |
main
| 4.333333 |
3;5;5
|
3;3;4
| null |
Distributionally Robust Recourse Action
| null | null | 3.333333 | 3.666667 |
Reject
|
5;3;3
|
1;2;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
graph neural network;graph representation learning;attention weighting;walk aggregation;representation power;learning guarantees;interpretability
| null | 2.75 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
5;5;5;5
|
3;4;3;3
| null |
An Analysis of Attentive Walk-Aggregating Graph Neural Networks
| null | null | 3.25 | 4 |
Withdraw
|
4;4;4;4
|
2;3;3;3
|
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