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values |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
null |
The Ohio State University, USA
|
2022
| 2.666667 |
https://iclr.cc/virtual/2022/poster/6129; None
| null | 0 | null | null | null |
3;3;2
| null |
Hong-You Chen, Wei-Lun Chao
|
https://iclr.cc/virtual/2022/poster/6129
|
federated learning;personalization;image classification
| null | 3 | null |
https://openreview.net/forum?id=I1hQbx10Kxn
|
iclr
| 0.866025 | 0 | null |
main
| 7 |
5;8;8
|
3;3;3
|
https://iclr.cc/virtual/2022/poster/6129
|
On Bridging Generic and Personalized Federated Learning for Image Classification
| null | null | 3 | 3 |
Spotlight
|
2;4;3
|
3;3;3
|
null |
Layer 6 AI
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/7197; None
| null | 0 | null | null | null |
2;4;3;2
| null |
Xiao Shi (Gary) Huang, Felipe Perez, Maksims Volkovs
|
https://iclr.cc/virtual/2022/poster/7197
|
Natural Language Processing;Deep Learning;Non-autoregressive Machine Translation;Transformer;Distillation
| null | 2 | null |
https://openreview.net/forum?id=I2Hw58KHp8O
|
iclr
| 0 | 0.816497 | null |
main
| 6.75 |
3;8;8;8
|
2;3;3;4
|
https://iclr.cc/virtual/2022/poster/7197
|
Improving Non-Autoregressive Translation Models Without Distillation
|
https://github.com/layer6ai-labs/CMLMC
| null | 3 | 4 |
Poster
|
4;4;4;4
|
2;3;0;3
|
null | null |
2022
| 1.25 | null | null | 0 | null | null | null |
1;1;1;2
| null | null | null |
Graph neural network;dynamic graph neural network;link prediction;dynamic link prediction;temporal graph
| null | 2.5 | null | null |
iclr
| 0 | -0.707107 | null |
main
| 3 |
1;3;3;5
|
4;4;3;3
| null |
Benchmarking Graph Neural Networks on Dynamic Link Prediction
| null | null | 3.5 | 4.25 |
Withdraw
|
4;5;4;4
|
2;3;3;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null | null | null | 2 | null | null |
iclr
| -0.174078 | 0.98644 | null |
main
| 4.25 |
3;3;5;6
|
2;2;3;4
| null |
Towards Axiomatic, Hierarchical, and Symbolic Explanation for Deep Models
| null | null | 2.75 | 3.75 |
Withdraw
|
3;5;3;4
|
2;2;2;2
|
null |
Qualcomm AI Research
|
2022
| 3.2 |
https://iclr.cc/virtual/2022/poster/7095; None
| null | 0 | null | null | null |
3;3;4;2;4
| null |
Yinhao Zhu, Yang Yang, Taco Cohen
|
https://iclr.cc/virtual/2022/poster/7095
|
transformer;transform coding;image compression;video compression
| null | 3.6 | null |
https://openreview.net/forum?id=IDwN6xjHnK8
|
iclr
| -0.327327 | -0.408248 | null |
main
| 7.2 |
6;6;8;8;8
|
4;4;4;3;4
|
https://iclr.cc/virtual/2022/poster/7095
|
Transformer-based Transform Coding
| null | null | 3.8 | 4.2 |
Poster
|
4;5;5;4;3
|
3;4;4;4;3
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;3;3;3
| null | null | null |
Discrete energy-based models;ratio matching;importance sampling;gradient
| null | 2.5 | null | null |
iclr
| 0.57735 | 1 | null |
main
| 5.75 |
5;6;6;6
|
3;4;4;4
| null |
Gradient-Guided Importance Sampling for Learning Discrete Energy-Based Models
| null | null | 3.75 | 4 |
Reject
|
3;3;5;5
|
3;2;3;2
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
3;3;3;2
| null | null | null |
fMRI;graph neural networks;feature attribution
| null | 2.75 | null | null |
iclr
| 0 | 0 | null |
main
| 5.5 |
5;5;6;6
|
3;3;3;3
| null |
Deep Representations for Time-varying Brain Datasets
| null | null | 3 | 4 |
Reject
|
4;4;4;4
|
2;3;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
Unsupervised Domain Adaptation;Self-Training;Semantic Segmentation;Multimodal Learning
| null | 1.75 | null | null |
iclr
| 0 | 0 | null |
main
| 3 |
3;3;3;3
|
2;3;2;2
| null |
Unsupervised Domain Adaptation Via Pseudo-labels And Objectness Constraints
| null | null | 2.25 | 4.25 |
Withdraw
|
4;4;4;5
|
2;2;1;2
|
null |
Paper under double-blind review
|
2022
| 2.25 | null | null | 0 | null | null | null |
2;3;2;2
| null | null | null | null | null | 1.5 | null | null |
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6;6
|
2;4;3;3
| null |
SoftHebb: Bayesian inference in unsupervised Hebbian soft winner-take-all networks
| null | null | 3 | 3.75 |
Reject
|
3;4;4;4
|
2;0;2;2
|
null |
Purdue University; DeepMind
|
2022
| 3.5 |
https://iclr.cc/virtual/2022/poster/7052; None
| null | 0 | null | null | null |
3;4;4;3
| null |
Wei Deng, Siqi Liang, Botao Hao, Guang Lin, Faming Liang
|
https://iclr.cc/virtual/2022/poster/7052
|
stochastic gradient Langevin dynamics;MCMC;importance sampling;Wang-Landau algorithm;Parallel MCMC Methods;stochastic approximation
| null | 3.5 | null |
https://openreview.net/forum?id=IK9ap6nxXr2
|
iclr
| -0.333333 | 0.333333 | null |
main
| 6.5 |
6;6;6;8
|
4;2;4;4
|
https://iclr.cc/virtual/2022/poster/7052
|
Interacting Contour Stochastic Gradient Langevin Dynamics
| null | null | 3.5 | 3.25 |
Poster
|
3;4;3;3
|
3;4;4;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
knowledge-based VQA
| null | 2.75 | null | null |
iclr
| 0.816497 | -0.57735 | null |
main
| 5.25 |
5;5;5;6
|
4;4;3;3
| null |
Breaking Down Questions for Outside-Knowledge VQA
| null | null | 3.5 | 4 |
Withdraw
|
3;4;4;5
|
3;2;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
out-of-distribution detection;outlier detection;adversarial attack;model evaluation;markov chain monte carlo
| null | 2.5 | null | null |
iclr
| 0 | 1 | null |
main
| 4.5 |
3;3;6;6
|
2;2;4;4
| null |
Adversarial Distributions Against Out-of-Distribution Detectors
| null | null | 3 | 3.5 |
Reject
|
4;3;3;4
|
2;2;3;3
|
null |
Under double-blind review
|
2022
| 1.25 | null | null | 0 | null | null | null |
1;2;1;1
| null | null | null |
polysemy;natural language processing;classification;language model;BERT;data visualization;Korean
| null | 1.5 | null | null |
iclr
| 1 | 0.57735 | null |
main
| 2.5 |
1;3;3;3
|
2;2;3;3
| null |
How does BERT address polysemy of Korean adverbial postpositions -ey, -eyse, and -(u)lo?
| null | null | 2.5 | 3.75 |
Reject
|
3;4;4;4
|
2;1;2;1
|
null | null |
2022
| 0 | null | null | 0 | null | null | null | null | null | null | null |
I-pomdps;Belief propagation;Multi-agent control
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 0 | null | null | null |
Multi-Agent Decentralized Belief Propagation on Graphs
| null | null | 0 | 0 |
Desk Reject
| null | null |
null | null |
2022
| 2.6 | null | null | 0 | null | null | null |
2;2;3;3;3
| null | null | null |
Weak Supervision;Active Learning;Fuzzy logic;AI in Healthcare
| null | 2.8 | null | null |
iclr
| 0.080064 | 0.166667 | null |
main
| 5.4 |
5;5;5;6;6
|
4;3;3;4;3
| null |
ACTIVE REFINEMENT OF WEAKLY SUPERVISED MODELS
| null | null | 3.4 | 3.4 |
Reject
|
3;5;2;4;3
|
2;3;3;3;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;3;2
| null | null | null |
reinforcement learning;policy gradient;learning rate
| null | 2.25 | null | null |
iclr
| -0.100504 | -0.100504 | null |
main
| 4.75 |
1;5;5;8
|
3;2;2;3
| null |
Batch size-invariance for policy optimization
| null | null | 2.5 | 4.5 |
Reject
|
5;4;4;5
|
2;2;3;2
|
null | null |
2022
| 2.4 | null | null | 0 | null | null | null |
2;2;2;3;3
| null | null | null | null | null | 2 | null | null |
iclr
| -0.790569 | 0.952579 | null |
main
| 4.4 |
3;3;5;5;6
|
2;2;3;3;3
| null |
Dict-BERT: Enhancing Language Model Pre-training with Dictionary
| null | null | 2.6 | 4 |
Withdraw
|
4;5;4;4;3
|
2;0;2;3;3
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;3;3
| null | null | null |
sparse transformer;robustness;language model;dropout;regularization
| null | 2.333333 | null | null |
iclr
| -0.755929 | 0.944911 | null |
main
| 4.666667 |
3;5;6
|
2;3;3
| null |
ERNIE-SPARSE: Robust Efficient Transformer Through Hierarchically Unifying Isolated Information
| null | null | 2.666667 | 4.666667 |
Withdraw
|
5;5;4
|
2;2;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;1;1;3;3
| null | null | null |
loss function landscape;loss function;AUC;area under the curve;alternative loss functions;loss function visualisation
| null | 2 | null | null |
iclr
| -0.633866 | 0.645497 | null |
main
| 4 |
3;3;3;5;6
|
2;2;3;3;3
| null |
Characterising the Area Under the Curve Loss Function Landscape
| null | null | 2.6 | 3.2 |
Reject
|
3;4;4;2;3
|
2;1;2;2;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;3;2
| null | null | null |
molecular optimization;molecular generation;drug discovery;reinforcement learning
| null | 2.25 | null | null |
iclr
| 0 | 0 | null |
main
| 4.5 |
3;3;6;6
|
3;3;3;3
| null |
Fragment-Based Sequential Translation for Molecular Optimization
| null | null | 3 | 4 |
Reject
|
4;4;4;4
|
2;0;4;3
|
null |
The Chinese University of Hong Kong, Shenzhen; Monash University; The University of Texas at Austin; Xidian University
|
2022
| 2.25 |
https://iclr.cc/virtual/2022/poster/6840; None
| null | 0 | null | null | null |
2;2;2;3
| null |
dongsheng wang, Dandan Guo, He Zhao, Huangjie Zheng, Korawat Tanwisuth, Bo Chen, Mingyuan Zhou
|
https://iclr.cc/virtual/2022/poster/6840
|
topic model;text mining;distribution matching
| null | 2 | null |
https://openreview.net/forum?id=IYMuTbGzjFU
|
iclr
| -0.333333 | 0 | null |
main
| 5.25 |
5;5;5;6
|
3;3;3;3
|
https://iclr.cc/virtual/2022/poster/6840
|
Representing Mixtures of Word Embeddings with Mixtures of Topic Embeddings
| null | null | 3 | 4.25 |
Poster
|
5;4;4;4
|
3;0;2;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;3;2
| null | null | null |
few-shot learning;few-shot segmentation;segmentation;gaussian processes
| null | 2.25 | null | null |
iclr
| -0.57735 | 0 | null |
main
| 5.75 |
5;6;6;6
|
3;3;3;3
| null |
Dense Gaussian Processes for Few-Shot Segmentation
| null | null | 3 | 4.5 |
Reject
|
5;5;4;4
|
2;3;2;2
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
data augmentation;consistency regularization;generalization bound
| null | 2.25 | null | null |
iclr
| 0 | -0.132453 | null |
main
| 4.75 |
3;5;5;6
|
3;3;2;3
| null |
Theoretical Analysis of Consistency Regularization with Limited Augmented Data
| null | null | 2.75 | 4 |
Reject
|
4;4;4;4
|
1;2;2;4
|
null |
University of Salzburg; University of Konstanz; IBM-MIT Watson AI Lab; University of Frankfurt
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/5925; None
| null | 0 | null | null | null |
3;3;2;4
| null |
Felix Petersen, Christian Borgelt, Hilde Kuehne, Oliver Deussen
|
https://iclr.cc/virtual/2022/poster/5925
|
differentiable sorting;monotonic;sorting;ranking;sorting networks
| null | 2.5 | null |
https://openreview.net/forum?id=IcUWShptD7d
|
iclr
| 0.324443 | 0.662266 | null |
main
| 6.25 |
5;6;6;8
|
3;4;4;4
|
https://iclr.cc/virtual/2022/poster/5925
|
Monotonic Differentiable Sorting Networks
| null | null | 3.75 | 3 |
Poster
|
2;4;3;3
|
2;3;2;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;1;3
| null | null | null |
Imbalanced Regression;Bayesian Debiasing
| null | 2.333333 | null | null |
iclr
| -0.188982 | 0.755929 | null |
main
| 4.666667 |
3;5;6
|
2;2;3
| null |
Bayesian Imbalanced Regression Debiasing
| null | null | 2.333333 | 3.333333 |
Withdraw
|
4;2;4
|
2;2;3
|
null |
Microsoft Research New England; Department of Computer Science, Harvard University and Department of EECS, MIT
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/6234; None
| null | 0 | null | null | null |
3;3;2;2
| null |
Raaz Dwivedi, Lester Mackey
|
https://iclr.cc/virtual/2022/poster/6234
|
coresets;maximum mean discrepancy;Markov chain Monte Carlo;reproducing kernel Hilbert space;thinning;compression
| null | 1.5 | null |
https://openreview.net/forum?id=IfNu7Dr-3fQ
|
iclr
| -0.688247 | 0.132453 | null |
main
| 6.25 |
5;6;6;8
|
4;4;3;4
|
https://iclr.cc/virtual/2022/poster/6234
|
Generalized Kernel Thinning
| null | null | 3.75 | 2.5 |
Poster
|
3;2;3;2
|
2;2;0;2
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null | null | null | 1.25 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
5;5;5;5
|
4;3;3;3
| null |
Can Reinforcement Learning Efficiently Find Stackelberg-Nash Equilibria in General-Sum Markov Games?
| null | null | 3.25 | 3 |
Reject
|
4;3;3;2
|
0;3;0;2
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
3;2;2;3
| null | null | null |
recommender systems;sequential behavior modeling
| null | 2.75 | null | null |
iclr
| 0 | -0.333333 | null |
main
| 5.25 |
5;5;5;6
|
3;4;3;3
| null |
Iterative Memory Network for Long Sequential User Behavior Modeling in Recommender Systems
| null | null | 3.25 | 4 |
Reject
|
4;4;4;4
|
2;2;3;4
|
null | null |
2022
| 1.5 | null | null | 0 | null | null | null |
1;2;1;2
| null | null | null |
Experience Replay More;Key Transitions;Sampling;Add Noise to Noise;Deep Reinforcement Learning
| null | 1.75 | null | null |
iclr
| 0.57735 | 0.301511 | null |
main
| 2 |
1;1;3;3
|
1;2;1;3
| null |
Experience Replay More When It's a Key Transition in Deep Reinforcement Learning
| null | null | 1.75 | 4.25 |
Reject
|
4;4;4;5
|
2;2;1;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;3;2
| null | null | null |
Decision Tree;Stochastic Optimization;Haar Filters;Haar Cascade
| null | 2 | null | null |
iclr
| 0 | 0 | null |
main
| 3 |
3;3;3;3
|
2;2;2;2
| null |
Stochastic Induction of Decision Trees with Application to Learning Haar Tree
| null | null | 2 | 3.5 |
Reject
|
4;3;4;3
|
3;2;0;3
|
null |
UBC; University of Edinburgh; UBC and Amii
|
2022
| 3.25 |
https://iclr.cc/virtual/2022/poster/6630; None
| null | 0 | null | null | null |
3;3;3;4
| null |
YI REN, Shangmin Guo, Danica J Sutherland
|
https://iclr.cc/virtual/2022/poster/6630
|
Classification;Supervision;Knowledge Distillation
| null | 3 | null |
https://openreview.net/forum?id=Iog0djAdbHj
|
iclr
| 0.777778 | 0.96225 | null |
main
| 6.75 |
5;6;8;8
|
2;2;3;3
|
https://iclr.cc/virtual/2022/poster/6630
|
Better Supervisory Signals by Observing Learning Paths
| null | null | 2.5 | 3.75 |
Poster
|
3;4;4;4
|
2;3;3;4
|
null |
Google Brain; Baidu Apollo; DeepMind; University of Toronto, Vector Institute
|
2022
| 2.666667 |
https://iclr.cc/virtual/2022/poster/5961; None
| null | 0 | null | null | null |
3;2;3
| null |
Shengyang Sun, Daniele Calandriello, Huiyi Hu, Ang Li, Michalis Titsias
|
https://iclr.cc/virtual/2022/poster/5961
|
Task-free continual learning;replay memory;information theoretic;reservoir sampling
| null | 2.666667 | null |
https://openreview.net/forum?id=IpctgL7khPp
|
iclr
| 0.755929 | 0.188982 | null |
main
| 6.333333 |
5;6;8
|
4;3;4
|
https://iclr.cc/virtual/2022/poster/5961
|
Information-theoretic Online Memory Selection for Continual Learning
| null | null | 3.666667 | 3.666667 |
Poster
|
3;4;4
|
3;2;3
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;2;3;4
| null | null | null |
Regularization;Hessian Trace;Stochastic Estimator;Nonlinear Dynamical System;Generalization Error
| null | 1.75 | null | null |
iclr
| -0.70014 | 0.37998 | null |
main
| 5.25 |
3;5;5;8
|
2;2;4;3
| null |
Regularizing Deep Neural Networks with Stochastic Estimators of Hessian Trace
| null | null | 2.75 | 3.5 |
Reject
|
4;3;4;3
|
1;2;2;2
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
targeted environment design;offline reinforcement learning;deep learning;adversarial learning
| null | 2.5 | null | null |
iclr
| -0.800641 | -0.800641 | null |
main
| 5.5 |
3;5;6;8
|
4;3;3;3
| null |
Targeted Environment Design from Offline Data
| null | null | 3.25 | 4.25 |
Reject
|
5;4;4;4
|
2;3;2;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;2;3
| null | null | null |
predictive learning;object-centric representation;3D perception;sensory grounding
| null | 2.5 | null | null |
iclr
| -0.140028 | -0.727607 | null |
main
| 5.25 |
3;5;5;8
|
4;3;3;3
| null |
Learning to perceive objects by prediction
| null | null | 3.25 | 3.5 |
Reject
|
3;4;4;3
|
3;2;2;3
|
null |
KAIST, Daejeon, South Korea
|
2022
| 3.25 |
https://iclr.cc/virtual/2022/poster/6360; None
| null | 0 | null | null | null |
3;4;3;3
| null |
Junyoung Park, Jinhyun Choo, Jinkyoo Park
|
https://iclr.cc/virtual/2022/poster/6360
|
Graph;Graph Neural Network;Fixed point;Implicit model;Implicit function theorem;Convergent
| null | 2 | null |
https://openreview.net/forum?id=ItkxLQU01lD
|
iclr
| 0 | 0 | null |
main
| 8 |
8;8;8;8
|
4;4;3;4
|
https://iclr.cc/virtual/2022/poster/6360
|
Convergent Graph Solvers
|
https://github.com/Junyoungpark/CGS
| null | 3.75 | 4.25 |
Poster
|
4;4;4;5
|
3;0;2;3
|
null |
Department of ECE, University of Utah, Salt Lake City, UT 84112, USA
|
2022
| 2.6 |
https://iclr.cc/virtual/2022/poster/6982; None
| null | 0 | null | null | null |
2;3;3;2;3
| null |
Ziyi Chen, Shaocong Ma, Yi Zhou
|
https://iclr.cc/virtual/2022/poster/6982
|
Two-player Zero-sum Markov game;Entropy regularization;Policy extragradient;Nash equilibrium;Sample complexity
| null | 0 | null |
https://openreview.net/forum?id=IvepFxYRDG
|
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6;6;6
|
4;4;4;3;4
|
https://iclr.cc/virtual/2022/poster/6982
|
Sample Efficient Stochastic Policy Extragradient Algorithm for Zero-Sum Markov Game
| null | null | 3.8 | 3.4 |
Poster
|
4;4;3;3;3
| null |
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
3;3;2
| null | null | null |
Integrated Gradients;Expected Gradients;Explainable AI;Integrated Certainty Gradients;Attribution
| null | 1.666667 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
5;5;5
|
3;2;4
| null |
Exploring unfairness in Integrated Gradients based attribution methods
| null | null | 3 | 3 |
Reject
|
3;2;4
|
2;2;1
|
null |
Mila, Université de Montréal
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6496; None
| null | 0 | null | null | null |
3;3;3;3
| null |
Sarthak Mittal, Sharath Chandra Raparthy, Irina Rish, Yoshua Bengio, Guillaume Lajoie
|
https://iclr.cc/virtual/2022/poster/6496
|
compositional attention;flexible search and retrieval;better generalization
| null | 3 | null |
https://openreview.net/forum?id=IwJPj2MBcIa
|
iclr
| 0.57735 | 1 | null |
main
| 7 |
6;6;8;8
|
3;3;4;4
|
https://iclr.cc/virtual/2022/poster/6496
|
Compositional Attention: Disentangling Search and Retrieval
|
https://github.com/sarthmit/Compositional-Attention
| null | 3.5 | 3.25 |
Spotlight
|
3;3;4;3
|
3;3;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
Deep Directed Graphical Models;Knowledge Distillation;Reparameterization trick;Model compression
| null | 2 | null | null |
iclr
| -0.57735 | 0.333333 | null |
main
| 5.25 |
5;5;5;6
|
3;2;3;3
| null |
A Unified Knowledge Distillation Framework for Deep Directed Graphical Models
| null | null | 2.75 | 3.5 |
Reject
|
3;4;4;3
|
2;2;2;2
|
null |
AWS AI Labs; Technical University of Denmark; Zalando SE
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/6757; None
| null | 0 | null | null | null |
2;3;3;2
| null |
Paul Jeha, Michael Bohlke-Schneider, Pedro Mercado, Shubham Kapoor, Rajbir Nirwan, Valentin Flunkert, Jan Gasthaus, Tim Januschowski
|
https://iclr.cc/virtual/2022/poster/6757
|
Synthetic Time Series;GAN;Generative Modeling;Time Series;Forecasting
| null | 2.75 | null |
https://openreview.net/forum?id=Ix_mh42xq5w
|
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6;6
|
3;4;4;4
|
https://iclr.cc/virtual/2022/poster/6757
|
PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series
| null | null | 3.75 | 3.75 |
Poster
|
4;3;3;5
|
2;3;3;3
|
null |
Mila, Université de Montréal; Apple Inc.
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6511; None
| null | 0 | null | null | null |
3;3;3
| null |
Ruixiang Zhang, Shuangfei Zhai, Etai Littwin, Joshua Susskind
|
https://iclr.cc/virtual/2022/poster/6511
| null | null | 2.666667 | null |
https://openreview.net/forum?id=J1rhANsCY9
|
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6
|
3;4;3
|
https://iclr.cc/virtual/2022/poster/6511
|
Learning Representation from Neural Fisher Kernel with Low-rank Approximation
| null | null | 3.333333 | 3.666667 |
Poster
|
4;3;4
|
2;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;2;4
| null | null | null |
distribution shift;test time adaptation;data augmentation
| null | 2.75 | null | null |
iclr
| 0.408248 | -0.187317 | null |
main
| 6 |
5;5;6;8
|
3;4;1;3
| null |
Test Time Robustification of Deep Models via Adaptation and Augmentation
| null | null | 2.75 | 4.5 |
Reject
|
4;5;4;5
|
2;2;3;4
|
null |
Department of Electrical and Computer Engineering, Princeton University, NJ 08544, USA; Department of Computer Science, Cornell University, Ithaca, NY 14850, USA
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/7191; None
| null | 0 | null | null | null |
2;3;3;4
| null |
Masatoshi Uehara, Xuezhou Zhang, Wen Sun
|
https://iclr.cc/virtual/2022/poster/7191
|
Provably sample efficient Reinforcement Learning;PAC bounds;Representation learning;Low-rank MDP
| null | 0.5 | null |
https://openreview.net/forum?id=J4iSIR9fhY0
|
iclr
| 0 | 0.19245 | null |
main
| 6.75 |
5;6;8;8
|
3;4;3;4
|
https://iclr.cc/virtual/2022/poster/7191
|
Representation Learning for Online and Offline RL in Low-rank MDPs
| null | null | 3.5 | 4 |
Spotlight
|
4;4;4;4
|
2;0;0;0
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;2;4;3
| null | null | null | null | null | 1.75 | null | null |
iclr
| -1 | 0 | null |
main
| 4 |
3;3;5;5
|
3;2;3;2
| null |
Mutual Information Estimation as a Difference of Entropies for Unsupervised Representation Learning
| null | null | 2.5 | 3.5 |
Withdraw
|
4;4;3;3
|
3;2;0;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
Weight Decay;Regularization;Optimization;Deep Learning
| null | 2.5 | null | null |
iclr
| -0.272166 | 0.316228 | null |
main
| 5 |
3;3;6;8
|
3;2;1;4
| null |
Understanding and Scheduling Weight Decay
| null | null | 2.5 | 3.5 |
Reject
|
4;4;2;4
|
2;2;3;3
|
null |
Universit é Côte d’Azur, Inria (Maasai team), Laboratoire J.A. Dieudonn é, CNRS, France; Department of Applied Mathematics and Computer Science, Technical University of Denmark, Denmark
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/5973; None
| null | 0 | null | null | null |
2;2;3;3
| null |
Niels Ipsen, Pierre-Alexandre Mattei, Jes Frellsen
|
https://iclr.cc/virtual/2022/poster/5973
| null | null | 2.5 | null |
https://openreview.net/forum?id=J7b4BCtDm4
|
iclr
| 0 | 1 | null |
main
| 6.5 |
5;5;8;8
|
3;3;4;4
|
https://iclr.cc/virtual/2022/poster/5973
|
How to deal with missing data in supervised deep learning?
| null | null | 3.5 | 3.5 |
Poster
|
4;3;4;3
|
2;2;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;4;2
| null | null | null |
search space;sparsity;neural models;deep learning
| null | 2.75 | null | null |
iclr
| 1 | 0.57735 | null |
main
| 5.5 |
5;5;6;6
|
3;3;4;3
| null |
Search Spaces for Neural Model Training
| null | null | 3.25 | 3.5 |
Reject
|
3;3;4;4
|
3;2;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null | null | null | 2.25 | null | null |
iclr
| -0.688247 | 0.899229 | null |
main
| 4.75 |
3;5;5;6
|
2;3;4;4
| null |
Diverse and Consistent Multi-view Networks for Semi-supervised Regression
| null | null | 3.25 | 3.5 |
Reject
|
4;4;3;3
|
2;2;2;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
3;2;2;3
| null | null | null |
Generative Adversarial Networks;Text-to-Image Generation;Memory Bank;Semi-parametric
| null | 2.75 | null | null |
iclr
| -0.408248 | 0.866025 | null |
main
| 5 |
3;5;6;6
|
2;3;4;3
| null |
Memory-Driven Text-to-Image Generation
| null | null | 3 | 3.5 |
Withdraw
|
4;3;3;4
|
2;3;3;3
|
null |
Sainsbury Wellcome Centre, UCL; Gatsby Unit, UCL
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6717; None
| null | 0 | null | null | null |
2;2;4;4
| null |
Ted Moskovitz, Spencer Wilson, Maneesh Sahani
|
https://iclr.cc/virtual/2022/poster/6717
|
successor representation;successor features;generalized policy improvement;GPI
| null | 2.5 | null |
https://openreview.net/forum?id=JBAZe2yN6Ub
|
iclr
| 0 | 0.96225 | null |
main
| 6.75 |
5;6;8;8
|
3;3;4;4
|
https://iclr.cc/virtual/2022/poster/6717
|
A First-Occupancy Representation for Reinforcement Learning
| null | null | 3.5 | 4 |
Poster
|
4;4;4;4
|
2;2;2;4
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
Explainable AI;Faithfulness;Robustness;Variational inference
| null | 2.25 | null | null |
iclr
| -0.707107 | 0.57735 | null |
main
| 4 |
3;3;5;5
|
3;2;3;3
| null |
Variational Perturbations for Visual Feature Attribution
| null | null | 2.75 | 4 |
Withdraw
|
5;4;3;4
|
2;2;2;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;3;2;2
| null | null | null | null | null | 2.25 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
5;5;5;5
|
3;3;3;3
| null |
Enforcing physics-based algebraic constraints for inference of PDE models on unstructured grids
| null | null | 3 | 4 |
Reject
|
4;4;4;4
|
2;3;2;2
|
null |
Universität Zürich, Department of Informatics; Universität Basel, Departement Mathematik und Informatik
|
2022
| 3.333333 |
https://iclr.cc/virtual/2022/poster/6477; None
| null | 0 | null | null | null |
3;3;4
| null |
Anastasis Kratsios, Behnoosh Zamanlooy, Tianlin Liu, Ivan Dokmanic
|
https://iclr.cc/virtual/2022/poster/6477
|
Constrained Universal Approximation;Probabilistic Attention;Transformer Networks;Geometric Deep Learning;Measurable Maximum Theorem;Non-Affine Random Projections;Optimal Transport.
| null | 1.333333 | null |
https://openreview.net/forum?id=JGO8CvG5S9
|
iclr
| 0 | 0.866025 | null |
main
| 8 |
6;8;10
|
3;3;4
|
https://iclr.cc/virtual/2022/poster/6477
|
Universal Approximation Under Constraints is Possible with Transformers
| null | null | 3.333333 | 3.333333 |
Spotlight
|
4;2;4
|
1;3;0
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;3;3
| null | null | null |
reinforcement learning;intrinsic motivation;exploration;multi-agent
| null | 2.666667 | null | null |
iclr
| 0 | 1 | null |
main
| 4.333333 |
3;5;5
|
3;4;4
| null |
Explore and Control with Adversarial Surprise
| null | null | 3.666667 | 4 |
Reject
|
4;4;4
|
2;3;3
|
null |
Technion, IIT; Meta AI Research
|
2022
| 3.25 |
https://iclr.cc/virtual/2022/poster/5972; None
| null | 0 | null | null | null |
3;4;3;3
| null |
Alon Berliner, Guy Rotman, Yossi Adi, Roi Reichart, Tamir Hazan
|
https://iclr.cc/virtual/2022/poster/5972
|
structured prediction;derivative-free optimization;variational autoencoder
| null | 3 | null |
https://openreview.net/forum?id=JJCjv4dAbyL
|
iclr
| 0.57735 | 0.57735 | null |
main
| 7.5 |
6;8;8;8
|
3;4;4;3
|
https://iclr.cc/virtual/2022/poster/5972
|
Learning Discrete Structured Variational Auto-Encoder using Natural Evolution Strategies
| null | null | 3.5 | 3.5 |
Poster
|
3;4;4;3
|
3;4;2;3
|
null |
Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708, USA
|
2022
| 3.25 |
https://iclr.cc/virtual/2022/poster/7089; None
| null | 0 | null | null | null |
3;4;3;3
| null |
Juncheng Dong, Simiao Ren, Yang Deng, Omar Khatib, Jordan Malof, Mohammadreza Soltani, Willie Padilla, VAHID TAROKH
|
https://iclr.cc/virtual/2022/poster/7089
|
Blaschke Product;Neural Network;Phase Retrieval;Metamaterial;Meromorphic Functions
| null | 2.75 | null |
https://openreview.net/forum?id=JJxiD-kg-oK
|
iclr
| -0.132453 | 0.927173 | null |
main
| 6.25 |
5;6;6;8
|
3;3;3;4
|
https://iclr.cc/virtual/2022/poster/7089
|
Blaschke Product Neural Networks (BPNN): A Physics-Infused Neural Network for Phase Retrieval of Meromorphic Functions
| null | null | 3.25 | 3.25 |
Poster
|
3;3;4;3
|
2;3;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
Distributed machine learning;margin distribution;classification;kernel learning
| null | 2.5 | null | null |
iclr
| 0.57735 | 0 | null |
main
| 5.5 |
3;3;8;8
|
3;4;4;3
| null |
Distributed Optimal Margin Distribution Machine
| null | null | 3.5 | 3.75 |
Reject
|
4;3;4;4
|
2;2;3;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
3;2;2;2
| null | null | null |
imitation learning;optimal transport;GAIL;adversarial learning
| null | 2 | null | null |
iclr
| -0.333333 | 0.816497 | null |
main
| 4.5 |
3;5;5;5
|
2;3;4;3
| null |
Imitation Learning from Pixel Observations for Continuous Control
|
https://anonymous.4open.science/r/ImitateFromPixelsICLR-B0EF
| null | 3 | 3.75 |
Reject
|
4;4;4;3
|
2;2;2;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;1;2;3
| null | null | null |
recurrent neural network
| null | 1.5 | null | null |
iclr
| -0.174078 | -0.301511 | null |
main
| 2.5 |
1;1;3;5
|
3;2;3;2
| null |
Integrating Attention Feedback into the Recurrent Neural Network
| null | null | 2.5 | 3.75 |
Withdraw
|
4;4;3;4
|
1;1;2;2
|
null |
University of Maryland, College Park; Sun Yat-sen University
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/7130; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Yanchao Sun, Ruijie Zheng, Yongyuan Liang, Furong Huang
|
https://iclr.cc/virtual/2022/poster/7130
|
adversarial RL;robustness of RL;evasion attack;optimal attack;observation perturbation
| null | 2.75 | null |
https://openreview.net/forum?id=JM2kFbJvvI
|
iclr
| 0.863868 | 0.518321 | null |
main
| 6.25 |
3;6;8;8
|
2;4;3;3
|
https://iclr.cc/virtual/2022/poster/7130
|
Who Is the Strongest Enemy? Towards Optimal and Efficient Evasion Attacks in Deep RL
| null | null | 3 | 3 |
Poster
|
2;3;4;3
|
2;3;3;3
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
3;2;2;3;2;2
| null | null | null |
Strategy Optimization;Surface Realization;Task-oriented Dialogue
| null | 2.333333 | null | null |
iclr
| 0.707107 | 0.25 | null |
main
| 4.333333 |
3;3;5;5;5;5
|
2;3;3;3;2;3
| null |
Decoupling Strategy and Surface Realization for Task-oriented Dialogues
| null | null | 2.666667 | 3.5 |
Withdraw
|
3;3;4;4;4;3
|
3;2;2;3;2;2
|
null |
KAIST AI
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6815; None
| null | 0 | null | null | null |
3;2;3;3
| null |
Mingyu Kim, Kyeong Ryeol Go, Se-Young Yun
|
https://iclr.cc/virtual/2022/poster/6815
|
neural processes;stochastic attention;variational inference;information theory
| null | 2.5 | null |
https://openreview.net/forum?id=JPkQwEdYn8
|
iclr
| 0.229416 | -0.132453 | null |
main
| 6.25 |
5;6;6;8
|
3;4;3;3
|
https://iclr.cc/virtual/2022/poster/6815
|
Neural Processes with Stochastic Attention: Paying more attention to the context dataset
| null | null | 3.25 | 3 |
Poster
|
4;2;2;4
|
3;3;2;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
3;2;2;2
| null | null | null | null | null | 2.5 | null | null |
iclr
| -0.57735 | 0.57735 | null |
main
| 4 |
3;3;5;5
|
2;2;4;2
| null |
Kernel Density Decision Trees
| null | null | 2.5 | 4.25 |
Withdraw
|
4;5;4;4
|
3;2;2;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;2;3;4
| null | null | null |
geometric scattering;drug discovery;drug design;graph generation;autoencoder
| null | 2.5 | null | null |
iclr
| 0 | 0.946729 | null |
main
| 4.25 |
3;3;5;6
|
1;2;3;4
| null |
Molecular Graph Generation via Geometric Scattering
| null | null | 2.5 | 4 |
Withdraw
|
4;4;4;4
|
1;2;3;4
|
null |
Georgia Institute of Technology; Amazon; Google Brain; Siemens
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/7060; None
| null | 0 | null | null | null |
3;3;3;3
| null |
Haoran Sun, Hanjun Dai, Wei Xia, Arun Ramamurthy
|
https://iclr.cc/virtual/2022/poster/7060
| null | null | 3 | null |
https://openreview.net/forum?id=JSR-YDImK95
|
iclr
| 0 | 0 | null |
main
| 8 |
8;8;8;8
|
4;4;3;4
|
https://iclr.cc/virtual/2022/poster/7060
|
Path Auxiliary Proposal for MCMC in Discrete Space
| null | null | 3.75 | 4.5 |
Spotlight
|
5;5;3;5
|
3;3;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
Lab test responses;Patient Representation;Electronic Health Records
| null | 2 | null | null |
iclr
| 0.132453 | 0 | null |
main
| 4.75 |
3;5;5;6
|
3;3;3;3
| null |
PERSONALIZED LAB TEST RESPONSE PREDICTION WITH KNOWLEDGE AUGMENTATION
| null | null | 3 | 4.25 |
Reject
|
4;4;5;4
|
0;2;3;3
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
2;2;4
| null | null | null |
network pruning;convolutional neural network;deep learning
| null | 2.666667 | null | null |
iclr
| 0 | 0 | null |
main
| 3 |
3;3;3
|
2;2;2
| null |
Network Pruning Spaces
| null | null | 2 | 4 |
Withdraw
|
4;4;4
|
2;2;4
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
discrete blackbox optimization;mixed integer programming
| null | 2.75 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
3;5;6;6
|
3;4;3;3
| null |
Constrained Discrete Black-Box Optimization using Mixed-Integer Programming
| null | null | 3.25 | 4 |
Reject
|
4;4;4;4
|
2;2;4;3
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
2;3;3;4
| null | null | null | null | null | 2.5 | null | null |
iclr
| -0.333333 | -0.57735 | null |
main
| 4.5 |
3;5;5;5
|
4;4;3;3
| null |
A Dot Product Attention Free Transformer
| null | null | 3.5 | 3.75 |
Withdraw
|
4;3;4;4
|
2;3;2;3
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
4;2;2
| null | null | null |
Multi-Agent Reinforcement Learning;Sequential Social Dilemma;Cooperation Emergence
| null | 3 | null | null |
iclr
| -0.866025 | 0.5 | null |
main
| 3.666667 |
3;3;5
|
1;3;3
| null |
Learning Homophilic Incentives in Sequential Social Dilemmas
| null | null | 2.333333 | 4 |
Reject
|
4;5;3
|
4;2;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;3;2
| null | null | null | null | null | 2.25 | null | null |
iclr
| -0.522233 | 0.57735 | null |
main
| 4.5 |
3;5;5;5
|
3;4;4;3
| null |
Adaptive Behavior Cloning Regularization for Stable Offline-to-Online Reinforcement Learning
| null | null | 3.5 | 4.25 |
Reject
|
5;3;5;4
|
2;3;2;2
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;3;3
| null | null | null |
inverse reinforcement learning;one-class classification
| null | 2 | null | null |
iclr
| -0.327327 | 0.755929 | null |
main
| 4.666667 |
3;5;6
|
3;3;4
| null |
Deep Inverse Reinforcement Learning via Adversarial One-Class Classification
| null | null | 3.333333 | 3 |
Reject
|
3;4;2
|
2;2;2
|
null |
University of Rochester; Shanghai Jiao Tong University, Shanghai Qi Zhi Institute; DAMO Academy, Alibaba Group; Institute for AI Industry Research (AIR), Tsinghua University; Microsoft Research
|
2022
| 3.25 |
https://iclr.cc/virtual/2022/poster/7037; None
| null | 0 | null | null | null |
3;3;3;4
| null |
Cong Guo, Yuxian Qiu, Jingwen Leng, Xiaotian Gao, Chen Zhang, Yunxin Liu, Fan Yang, Yuhao Zhu, Minyi Guo
|
https://iclr.cc/virtual/2022/poster/7037
|
Data-Free Quantization;Hessian Matrix;Approximation
| null | 3 | null |
https://openreview.net/forum?id=JXhROKNZzOc
|
iclr
| -1 | 0.333333 | null |
main
| 6.5 |
6;6;6;8
|
2;3;3;3
|
https://iclr.cc/virtual/2022/poster/7037
|
SQuant: On-the-Fly Data-Free Quantization via Diagonal Hessian Approximation
|
https://github.com/clevercool/SQuant
| null | 2.75 | 3.75 |
Poster
|
4;4;4;3
|
3;3;3;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
Reinforcement learning;fairness;regret minimization;multi-objective optimization;constrained Markov decision processes
| null | 2.25 | null | null |
iclr
| 0 | 0 | null |
main
| 4 |
3;3;5;5
|
3;4;4;3
| null |
Reinforcement Learning with Ex-Post Max-Min Fairness
| null | null | 3.5 | 3 |
Reject
|
3;3;3;3
|
2;2;2;3
|
null |
Caltech; UC Berkeley
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6579; None
| null | 0 | null | null | null |
3;3;2;3
| null |
Alexander Pan, Kush Bhatia, Jacob Steinhardt
|
https://iclr.cc/virtual/2022/poster/6579
|
reward misspecification;reinforcement learning;reward hacking;alignment;ml safety
| null | 3.25 | null |
https://openreview.net/forum?id=JYtwGwIL7ye
|
iclr
| 0 | 0.333333 | null |
main
| 6.5 |
6;6;6;8
|
3;4;4;4
|
https://iclr.cc/virtual/2022/poster/6579
|
The Effects of Reward Misspecification: Mapping and Mitigating Misaligned Models
| null | null | 3.75 | 4 |
Poster
|
4;4;4;4
|
2;3;4;4
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;2;3;4
| null | null | null |
Image Clustering;Representation Learning;Self-supervised Learning
| null | 2.75 | null | null |
iclr
| -0.990148 | -0.70014 | null |
main
| 5.75 |
3;6;6;8
|
4;3;4;3
| null |
Exploring Non-Contrastive Representation Learning for Deep Clustering
| null | null | 3.5 | 4 |
Reject
|
5;4;4;3
|
2;3;3;3
|
null |
University of Massachusetts Amherst; Amherst College, University of Massachusetts Amherst
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/5996; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Li Ding, Lee Spector
|
https://iclr.cc/virtual/2022/poster/5996
|
deep learning;lexicase selection;optimization;evolutionary algorithms
| null | 2.25 | null |
https://openreview.net/forum?id=J_2xNmVcY4
|
iclr
| -0.522233 | 1 | null |
main
| 6.5 |
6;6;6;8
|
3;3;3;4
|
https://iclr.cc/virtual/2022/poster/5996
|
Optimizing Neural Networks with Gradient Lexicase Selection
| null | null | 3.25 | 3.75 |
Poster
|
3;5;4;3
|
1;2;2;4
|
null |
Apple
|
2022
| 2 |
https://iclr.cc/virtual/2022/poster/6260; None
| null | 0 | null | null | null |
2;2;2;2
| null |
Minsik Cho, Keivan Alizadeh-Vahid, Saurabh Adya, Mohammad Rastegari
|
https://iclr.cc/virtual/2022/poster/6260
|
Deep learning;neural network;compression
| null | 2.5 | null |
https://openreview.net/forum?id=J_F_qqCE3Z5
|
iclr
| 0 | -0.333333 | null |
main
| 5.75 |
5;6;6;6
|
3;2;3;3
|
https://iclr.cc/virtual/2022/poster/6260
|
DKM: Differentiable k-Means Clustering Layer for Neural Network Compression
| null | null | 2.75 | 4 |
Poster
|
4;4;4;4
|
2;2;3;3
|
null |
College of Computer Science, Zhejiang University of Technology, Hangzhou, China
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6446; None
| null | 0 | null | null | null |
3;3;3;3
| null |
Yuqi Liu, Bin Cao, JING FAN
|
https://iclr.cc/virtual/2022/poster/6446
|
Imbalance classification;Meta learning;Data weighting.
| null | 2.75 | null |
https://openreview.net/forum?id=J_PHjw4gvXJ
|
iclr
| -0.57735 | 0.57735 | null |
main
| 6.5 |
6;6;6;8
|
4;3;3;4
|
https://iclr.cc/virtual/2022/poster/6446
|
Improving the Accuracy of Learning Example Weights for Imbalance Classification
| null | null | 3.5 | 3.5 |
Poster
|
4;4;3;3
|
3;3;2;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
3;2;2;3
| null | null | null |
Federated Learning;variational inference
| null | 2.25 | null | null |
iclr
| 0.333333 | 0.816497 | null |
main
| 4.25 |
3;3;5;6
|
3;2;3;4
| null |
Federated Learning with Data-Agnostic Distribution Fusion
| null | null | 3 | 4.25 |
Withdraw
|
4;4;5;4
|
2;2;2;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;1;3
| null | null | null | null | null | 2 | null | null |
iclr
| -1 | 1 | null |
main
| 3.5 |
3;3;3;5
|
2;2;2;3
| null |
Variability of Neural Networks and Han-Layer: A Variability-Inspired Model
| null | null | 2.25 | 3.75 |
Reject
|
4;4;4;3
|
2;2;2;2
|
null | null |
2022
| 2.8 | null | null | 0 | null | null | null |
2;3;3;3;3
| null | null | null |
multi-label;privacy;voting;confidentiality;differential privacy;disributed collaboration;collaboration
| null | 2.4 | null | null |
iclr
| -0.300669 | -0.102062 | null |
main
| 5.2 |
3;5;5;5;8
|
3;3;4;4;3
| null |
Private Multi-Winner Voting For Machine Learning
| null | null | 3.4 | 2.8 |
Reject
|
4;2;2;3;3
|
3;2;2;2;3
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
2;3;3;4
| null | null | null |
deep learning;uncertainty estimation
| null | 2.5 | null | null |
iclr
| 0 | 0 | null |
main
| 5.5 |
5;5;6;6
|
2;4;2;4
| null |
DEUP: Direct Epistemic Uncertainty Prediction
| null | null | 3 | 3.5 |
Reject
|
3;4;3;4
|
2;3;3;2
|
null |
Brain Team, Google Research; Neurosciences Graduate Program, Stanford University
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6646; None
| null | 0 | null | null | null |
2;3;2;4
| null |
Gabriel Mel, Jeffrey Pennington
|
https://iclr.cc/virtual/2022/poster/6646
|
random feature models;high dimensional asymptotics;generalization;learning curves;double descent;multiple descent;alignment
| null | 1.75 | null |
https://openreview.net/forum?id=JfaWawZ8BmX
|
iclr
| 0.333333 | 1 | null |
main
| 6.5 |
6;6;6;8
|
3;3;3;4
|
https://iclr.cc/virtual/2022/poster/6646
|
Anisotropic Random Feature Regression in High Dimensions
| null | null | 3.25 | 3.75 |
Poster
|
4;4;3;4
|
2;2;3;0
|
null | null |
2022
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Few Shot Learning;Learning Instability
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 0 | null | null | null |
Few-Shot Multi-task Learning via Implicit regularization
| null | null | 0 | 0 |
Withdraw
| null | null |
null | null |
2022
| 2.4 | null | null | 0 | null | null | null |
2;3;2;3;2
| null | null | null | null | null | 2 | null | null |
iclr
| -0.845154 | 0.592927 | null |
main
| 4 |
3;3;3;5;6
|
3;1;2;3;3
| null |
Spatiotemporal Representation Learning on Time Series with Dynamic Graph ODEs
| null | null | 2.4 | 4.2 |
Withdraw
|
4;5;5;4;3
|
2;2;2;2;2
|
null |
Alibaba Group; BNRist, THUIBCS, KLISS, BLBCI, School of Software, Tsinghua University
|
2022
| 2.25 |
https://iclr.cc/virtual/2022/poster/6590; None
| null | 0 | null | null | null |
2;2;3;2
| null |
Yutong Feng, Jianwen Jiang, Mingqian Tang, Rong Jin, Yue Gao
|
https://iclr.cc/virtual/2022/poster/6590
|
Pre-Training;Contrastive Learning;Representation Learning;Downstream Transferring
| null | 2.25 | null |
https://openreview.net/forum?id=Jjcv9MTqhcq
|
iclr
| 0 | 0 | null |
main
| 5.75 |
5;6;6;6
|
3;2;4;3
|
https://iclr.cc/virtual/2022/poster/6590
|
Rethinking Supervised Pre-Training for Better Downstream Transferring
| null | null | 3 | 4 |
Poster
|
4;4;4;4
|
1;2;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
representation learning;product space
| null | 2.5 | null | null |
iclr
| 0 | 1 | null |
main
| 5.25 |
5;5;5;6
|
3;3;3;4
| null |
Switch Spaces: Learning Product Spaces with Sparse Gating
| null | null | 3.25 | 3 |
Withdraw
|
3;3;3;3
|
3;2;3;2
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;3;2
| null | null | null |
Variational Inference;Approximate Inference;MORE;VOGN;VIPS;GVA
| null | 2 | null | null |
iclr
| 0 | 1 | null |
main
| 4 |
3;3;6
|
2;2;3
| null |
A First-Order Method for Estimating Natural Gradients for Variational Inference with Gaussians and Gaussian Mixture Models
| null | null | 2.333333 | 4 |
Withdraw
|
4;4;4
|
2;2;2
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
2;3;3
| null | null | null |
generalization;neural networks;dynamics;double descent
| null | 2.666667 | null | null |
iclr
| -1 | 0.5 | null |
main
| 7 |
5;8;8
|
3;3;4
| null |
Multi-scale Feature Learning Dynamics: Insights for Double Descent
| null | null | 3.333333 | 4.333333 |
Reject
|
5;4;4
|
2;3;3
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
2;3;3
| null | null | null |
Time Series Forecasting;Graph Neural Networks;Graph Inference;Multivariate Time Series
| null | 1.666667 | null | null |
iclr
| -0.866025 | 1 | null |
main
| 4.333333 |
3;5;5
|
2;3;3
| null |
Multivariate Time Series Forecasting with Latent Graph Inference
| null | null | 2.666667 | 4 |
Reject
|
5;3;4
|
2;3;0
|
null |
NVIDIA; The University of Chicago
|
2022
| 3.25 |
https://iclr.cc/virtual/2022/poster/7183; None
| null | 0 | null | null | null |
4;3;3;3
| null |
Zhisheng Xiao, Karsten Kreis, Arash Vahdat
|
https://iclr.cc/virtual/2022/poster/7183
| null | null | 3.5 | null |
https://openreview.net/forum?id=JprM0p-q0Co
|
iclr
| 0 | 0 |
https://nvlabs.github.io/denoising-diffusion-gan
|
main
| 8 |
8;8;8;8
|
4;4;4;4
|
https://iclr.cc/virtual/2022/poster/7183
|
Tackling the Generative Learning Trilemma with Denoising Diffusion GANs
|
https://github.com/nvlabs/denoising-diffusion-gan
| null | 4 | 3.75 |
Spotlight
|
3;4;4;4
|
4;3;4;3
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;3;2
| null | null | null |
manifold learning;unsupervised learning;generative models;lie groups;transport operators;transformation learning
| null | 2.666667 | null | null |
iclr
| -1 | 0 | null |
main
| 5.333333 |
5;5;6
|
3;3;3
| null |
Learning Identity-Preserving Transformations on Data Manifolds
| null | null | 3 | 3.666667 |
Reject
|
4;4;3
|
2;4;2
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;3;2
| null | null | null |
safety;interpretability;explainability
| null | 2 | null | null |
iclr
| -0.132453 | 0.648886 | null |
main
| 4.75 |
3;5;5;6
|
2;4;3;3
| null |
On the Safety of Interpretable Machine Learning: A Maximum Deviation Approach
| null | null | 3 | 3.5 |
Reject
|
4;4;2;4
|
3;2;2;1
|
null |
DeepMind†; Google Research and DeepMind
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6303; None
| null | 0 | null | null | null |
2;3;3;3;4
| null |
Yi Tay, Vinh Tran, Sebastian Ruder, Jai Gupta, Hyung Won Chung, Dara Bahri, Zhen Qin, Simon Baumgartner, Cong Yu, Donald Metzler
|
https://iclr.cc/virtual/2022/poster/6303
|
transformers;NLP;language
| null | 2.8 | null |
https://openreview.net/forum?id=JtBRnrlOEFN
|
iclr
| 0.866025 | 0.9759 | null |
main
| 6 |
5;5;6;6;8
|
2;2;3;3;4
|
https://iclr.cc/virtual/2022/poster/6303
|
Charformer: Fast Character Transformers via Gradient-based Subword Tokenization
| null | null | 2.8 | 4 |
Poster
|
4;3;4;4;5
|
2;3;3;2;4
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null | null | null | 2 | null | null |
iclr
| 0.333333 | 0.57735 | null |
main
| 4.5 |
3;5;5;5
|
3;4;3;4
| null |
Intervention-based Recurrent Casual Model for Non-stationary Video Causal Discovery
| null | null | 3.5 | 4.25 |
Withdraw
|
4;4;4;5
|
2;2;2;2
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
Out-of-distribution Detection
| null | 2.75 | null | null |
iclr
| 0.57735 | 0.57735 | null |
main
| 5.5 |
5;5;6;6
|
3;3;3;4
| null |
Efficient Out-of-Distribution Detection via CVAE data Generation
| null | null | 3.25 | 3.75 |
Reject
|
4;3;4;4
|
2;3;3;3
|
null | null |
2022
| 0 | null | null | 0 | null | null | null | null | null | null | null |
reinforcement learning;model-based reinforcement learning;deep learning;bayesian deep learning;gaussian processes;continuous control;model uncertainty
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 0 | null | null | null |
Which model to trust: assessing the influence of models on the performance of reinforcement learning algorithms for continuous control tasks
| null | null | 0 | 0 |
Desk Reject
| null | null |
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
1;3;3;3
| null | null | null |
online algorithms;nonsymmetric determinantal point processes
| null | 2.75 | null | null |
iclr
| -0.973329 | 0.688247 | null |
main
| 4.75 |
3;5;5;6
|
2;2;3;3
| null |
Online MAP Inference and Learning for Nonsymmetric Determinantal Point Processes
| null | null | 2.5 | 4 |
Reject
|
5;4;4;3
|
2;3;3;3
|
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