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values |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;3;3
| null | null | null |
uncertainty estimation;semi-supervised learning;active learning
| null | 2.666667 | null | null |
iclr
| -1 | 0 | null |
main
| 3.666667 |
3;3;5
|
2;2;2
| null |
Vibration-based Uncertainty Estimation for Learning from Limited Supervision
| null | null | 2 | 3.666667 |
Withdraw
|
4;4;3
|
2;2;4
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
3;2;3;3
| null | null | null | null | null | 2.25 | null | null |
iclr
| 0.707107 | 0.904534 | null |
main
| 4 |
3;3;5;5
|
2;3;4;4
| null |
DP-InstaHide: Data Augmentations Provably Enhance Guarantees Against Dataset Manipulations
| null | null | 3.25 | 4 |
Withdraw
|
3;4;5;4
|
1;2;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
1;3;2;2
| null | null | null |
multi-agent reinforcement learning;language acquisition;emergent communication;acoustic communication;continuous signalling
| null | 1.5 | null | null |
iclr
| -0.333333 | 0.522233 | null |
main
| 3.5 |
3;3;3;5
|
2;4;3;4
| null |
Towards Learning to Speak and Hear Through Multi-Agent Communication over a Continuous Acoustic Channel
| null | null | 3.25 | 4.25 |
Reject
|
4;4;5;4
|
1;1;2;2
|
null |
University of California, Los Angeles; Centre for Perceptual and Interactive Intelligence; The Chinese University of Hong Kong
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6470; None
| null | 0 | null | null | null |
3;3;3;3
| null |
Quanyi Li, Zhenghao Peng, Bolei Zhou
|
https://iclr.cc/virtual/2022/poster/6470
|
Human in the Loop;Safe Reinforcement Learning;Autonomous Driving
| null | 3 | null |
https://openreview.net/forum?id=0cgU-BZp2ky
|
iclr
| 0 | -0.333333 | null |
main
| 6.5 |
6;6;6;8
|
4;3;3;3
|
https://iclr.cc/virtual/2022/poster/6470
|
Efficient Learning of Safe Driving Policy via Human-AI Copilot Optimization
|
https://decisionforce.github.io/HACO/
| null | 3.25 | 3 |
Poster
|
3;3;3;3
|
2;3;3;4
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;2;3
| null | null | null |
knowledge distillation;data augmentation;mixup;cutmix;model compression;active learning
| null | 2.666667 | null | null |
iclr
| -0.5 | 0.5 | null |
main
| 3.666667 |
3;3;5
|
3;2;3
| null |
Understanding the Success of Knowledge Distillation -- A Data Augmentation Perspective
| null | null | 2.666667 | 4.333333 |
Reject
|
5;4;4
|
3;2;3
|
null | null |
2022
| 1.333333 | null | null | 0 | null | null | null |
1;1;2
| null | null | null |
benchmarking;time-series classification;landscape analysis
| null | 2 | null | null |
iclr
| -0.5 | 1 | null |
main
| 4 |
3;3;6
|
2;2;3
| null |
Less is more: Selecting the right benchmarking set of data for time series classification
| null | null | 2.333333 | 3.333333 |
Withdraw
|
4;3;3
|
2;1;3
|
null |
Meta FAIR; National Energy Research Scientific Computing Center (NERSC)
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6800; None
| null | 0 | null | null | null |
3;3;2;3
| null |
Anuroop Sriram, Abhishek Das, Brandon Wood, Siddharth Goyal, Larry Zitnick
|
https://iclr.cc/virtual/2022/poster/6800
|
Graph Neural Networks;Atomic Simulations;Computational Chemistry
| null | 3.25 | null |
https://openreview.net/forum?id=0jP2n0YFmKG
|
iclr
| 0 | 0 | null |
main
| 6 |
5;5;6;8
|
3;3;3;3
|
https://iclr.cc/virtual/2022/poster/6800
|
Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations
| null | null | 3 | 2.25 |
Poster
|
1;3;3;2
|
3;3;3;4
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
Generative Adversarial Networks;Adversarial Traing;Latent Space
| null | 2.25 | null | null |
iclr
| -0.471405 | 0.866025 | null |
main
| 5 |
3;5;6;6
|
2;3;3;4
| null |
Improving Generative Adversarial Networks via Adversarial Learning in Latent Space
| null | null | 3 | 3.75 |
Reject
|
4;4;4;3
|
2;2;2;3
|
null |
Department of Anesthesiology, Department of Neuroscience, University of Wisconsin–Madison, USA; Department of Electrical and Computer Engineering, University of Wisconsin–Madison, USA; Department of Neurosurgery, Iowa Neuroscience Institute, University of Iowa, USA
|
2022
| 2.333333 |
https://iclr.cc/virtual/2022/poster/6706; None
| null | 0 | null | null | null |
2;2;3
| null |
Tananun Songdechakraiwut, Bryan Krause, Matthew Banks, Kirill Nourski, Barry Van Veen
|
https://iclr.cc/virtual/2022/poster/6706
|
Topological data analysis;cluster analysis;persistent homology;Wasserstein distance;Wasserstein barycenter;brain networks;intracranial electrophysiology;consciousness
| null | 2.333333 | null |
https://openreview.net/forum?id=0kPL3xO4R5
|
iclr
| 1 | 0.5 | null |
main
| 7.333333 |
6;8;8
|
3;4;3
|
https://iclr.cc/virtual/2022/poster/6706
|
Fast topological clustering with Wasserstein distance
|
https://github.com/topolearn
| null | 3.333333 | 4.666667 |
Poster
|
4;5;5
|
2;2;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
Continual learning;Task similarity;Catastrophic forgetting;Knowledge transfer
| null | 2 | null | null |
iclr
| -0.57735 | 0 | null |
main
| 4 |
3;3;5;5
|
2;4;3;3
| null |
Partially Relaxed Masks for Lightweight Knowledge Transfer without Forgetting in Continual Learning
| null | null | 3 | 3.75 |
Withdraw
|
4;4;3;4
|
2;2;2;2
|
null | null |
2022
| 1.666667 | null | null | 0 | null | null | null |
1;2;2
| null | null | null |
Neural network controlled systems;safety;verification;Taylor model arithmetic
| null | 1.666667 | null | null |
iclr
| -0.993399 | 0.917663 | null |
main
| 3.333333 |
1;3;6
|
2;2;3
| null |
POLAR: A Polynomial Arithmetic Framework for Verifying Neural-Network Controlled Systems
| null | null | 2.333333 | 4 |
Withdraw
|
5;4;3
|
1;2;2
|
null | null |
2022
| 1.6 | null | null | 0 | null | null | null |
1;2;1;2;2
| null | null | null |
Recommendation system;Neighborhood-based;Collaborative filtering;Data mining
| null | 1.8 | null | null |
iclr
| -0.422577 | 0.285714 | null |
main
| 2.6 |
1;1;3;3;5
|
3;2;2;4;3
| null |
Incorporating User-Item Similarity in Hybrid Neighborhood-based Recommendation System
| null | null | 2.8 | 4 |
Reject
|
4;4;5;4;3
|
1;1;2;2;3
|
null | null |
2022
| 1.666667 | null | null | 0 | null | null | null |
2;2;1
| null | null | null |
Reinforcement learning;multi-task learning;representation learning
| null | 1.666667 | null | null |
iclr
| 0 | 0 | null |
main
| 3 |
3;3;3
|
3;3;4
| null |
Generalizing Successor Features to continuous domains for Multi-task Learning
| null | null | 3.333333 | 4 |
Reject
|
4;4;4
|
2;2;1
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
3;2;3;3
| null | null | null |
Regression;Nearest Neighbor;Prototype Learning;Prototype Nearest Neighbor
| null | 2 | null | null |
iclr
| 0 | 0.57735 | null |
main
| 4 |
3;3;5;5
|
3;2;3;3
| null |
Synthetic Reduced Nearest Neighbor Model for Regression
| null | null | 2.75 | 3.5 |
Reject
|
3;4;4;3
|
3;2;3;0
|
null |
Computer Science Department, Stanford University, Stanford, CA, USA; Robotics Insitute & Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA, USA
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6697; None
| null | 0 | null | null | null |
3;3;3;3
| null |
Viraj Mehta, Biswajit Paria, Jeff Schneider, Stefano Ermon, Willie Neiswanger
|
https://iclr.cc/virtual/2022/poster/6697
|
reinforcement learning;acquisition function;information gain
| null | 2.75 | null |
https://openreview.net/forum?id=0no8Motr-zO
|
iclr
| -0.57735 | 0.57735 | null |
main
| 7.25 |
5;8;8;8
|
3;4;3;4
|
https://iclr.cc/virtual/2022/poster/6697
|
An Experimental Design Perspective on Model-Based Reinforcement Learning
| null | null | 3.5 | 3.5 |
Poster
|
4;3;4;3
|
3;3;3;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;1;3
| null | null | null | null | null | 2 | null | null |
iclr
| -0.816497 | 0.522233 | null |
main
| 3.75 |
3;3;3;6
|
2;4;3;4
| null |
Learning to Persuade
| null | null | 3.25 | 4 |
Reject
|
5;4;4;3
|
2;2;1;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
replay buffer;reinforcement learning;offline RL;attention
| null | 2.75 | null | null |
iclr
| 0 | 0.707107 | null |
main
| 5.5 |
5;5;6;6
|
2;3;4;3
| null |
Retrieval-Augmented Reinforcement Learning
| null | null | 3 | 3.5 |
Reject
|
3;4;3;4
|
2;2;4;3
|
null | null |
2022
| 3.25 | null | null | 0 | null | null | null |
3;3;3;4
| null | null | null |
dropout;generalization;PAC-Bayes
| null | 3.25 | null | null |
iclr
| -0.688247 | 0.229416 | null |
main
| 6.25 |
5;6;6;8
|
4;3;3;4
| null |
Weight Expansion: A New Perspective on Dropout and Generalization
| null | null | 3.5 | 3.5 |
Withdraw
|
4;4;3;3
|
3;3;3;4
|
null |
Georgia Institute of Technology; Duke University
|
2022
| 2.333333 |
https://iclr.cc/virtual/2022/poster/6311; None
| null | 0 | null | null | null |
2;2;3
| null |
Shixiang Zhu, Haoyun Wang, Zheng Dong, Xiuyuan Cheng, Yao Xie
|
https://iclr.cc/virtual/2022/poster/6311
| null | null | 1.333333 | null |
https://openreview.net/forum?id=0rcbOaoBXbg
|
iclr
| 0.114708 | 0.802955 | null |
main
| 5.666667 |
3;6;8
|
3;3;4
|
https://iclr.cc/virtual/2022/poster/6311
|
Neural Spectral Marked Point Processes
| null | null | 3.333333 | 3.333333 |
Poster
|
3;4;3
|
2;2;0
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
1;3;2;3
| null | null | null |
PU learning;Robust Generative Models;Lable noises
| null | 2.25 | null | null |
iclr
| 0 | 0.333333 | null |
main
| 4 |
1;5;5;5
|
3;3;3;4
| null |
Classify and Generate Reciprocally: Simultaneous Positive-Unlabelled Learning and Conditional Generation with Extra Data
| null | null | 3.25 | 4 |
Reject
|
4;4;3;5
|
2;2;2;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
neuroscience;brain-computer interfaces;practical attacks;adversarial attacks;EEGNet;edge computing;embedded systems
| null | 2.5 | null | null |
iclr
| -0.942809 | 0 | null |
main
| 5 |
3;3;6;8
|
3;3;3;3
| null |
Practical Adversarial Attacks on Brain--Computer Interfaces
| null | null | 3 | 4.5 |
Reject
|
5;5;4;4
|
2;2;3;3
|
null |
Department of Electrical Engineering, Technische Universität Darmstadt, Germany
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/7112; None
| null | 0 | null | null | null |
3;3;3;3
| null |
Kai Cui, Heinz Koeppl
|
https://iclr.cc/virtual/2022/poster/7112
|
Mean Field Games;Reinforcement Learning;Multi Agent Systems
| null | 2.5 | null |
https://openreview.net/forum?id=0sgntlpKDOz
|
iclr
| -0.942809 | 0.471405 | null |
main
| 6 |
5;5;6;8
|
4;3;4;4
|
https://iclr.cc/virtual/2022/poster/7112
|
Learning Graphon Mean Field Games and Approximate Nash Equilibria
| null | null | 3.75 | 3.75 |
Poster
|
4;4;4;3
|
2;2;2;4
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
Adversarial training;Adversarial examples;Minimax;Robustness
| null | 2.75 | null | null |
iclr
| 0.57735 | 0 | null |
main
| 4.5 |
3;3;6;6
|
3;4;4;3
| null |
Protect the weak: Class focused online learning for adversarial training
| null | null | 3.5 | 3.75 |
Reject
|
4;3;4;4
|
3;2;3;3
|
null |
Dept. of Comp. Sci. & Tech., Institute for AI, Tsinghua-Huawei Joint Center for AI, BNRist Center, State Key Lab for Intell. Tech. & Sys., Tsinghua University, Beijing, China; Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China
|
2022
| 3.4 |
https://iclr.cc/virtual/2022/poster/7166; None
| null | 0 | null | null | null |
4;3;4;3;3
| null |
Fan Bao, Chongxuan Li, Jun Zhu, Bo Zhang
|
https://iclr.cc/virtual/2022/poster/7166
|
diffusion probabilistic models;generative models
| null | 3 | null |
https://openreview.net/forum?id=0xiJLKH-ufZ
|
iclr
| 0 | 0 | null |
main
| 8 |
8;8;8;8;8
|
4;4;3;4;3
|
https://iclr.cc/virtual/2022/poster/7166
|
Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models
| null | null | 3.6 | 3.6 |
Oral
|
4;4;3;3;4
|
3;3;3;3;3
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;2;3
| null | null | null |
human-agent interaction;reinforcement learning;navigation
| null | 1.666667 | null | null |
iclr
| 0.5 | 0.5 | null |
main
| 3.666667 |
3;3;5
|
2;3;3
| null |
Learning When and What to Ask: a Hierarchical Reinforcement Learning Framework
| null | null | 2.666667 | 3.666667 |
Reject
|
4;3;4
|
1;1;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
3;2;2;3
| null | null | null |
Deep Learning;Neural Network Compression;Rate-Distortion Theories
| null | 0.75 | null | null |
iclr
| -0.662266 | 0.927173 | null |
main
| 4.75 |
3;5;5;6
|
2;3;3;3
| null |
Delving into Channels: Exploring Hyperparameter Space of Channel Bit Widths with Linear Complexity
| null | null | 2.75 | 4.75 |
Withdraw
|
5;5;5;4
|
0;1;2;0
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;2;3
| null | null | null |
belief propagation;neural networks;graphical models;gradient-free algorithms;discrete neural networks
| null | 2.25 | null | null |
iclr
| -0.800641 | 0.800641 | null |
main
| 5.5 |
3;5;6;8
|
3;3;3;4
| null |
Deep learning via message passing algorithms based on belief propagation
| null | null | 3.25 | 3.75 |
Reject
|
4;4;4;3
|
2;2;2;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
calibration;dirichlet kernel density estimation
| null | 2.25 | null | null |
iclr
| -0.522233 | -0.333333 | null |
main
| 5.75 |
5;5;5;8
|
3;3;4;3
| null |
Calibration Regularized Training of Deep Neural Networks using Kernel Density Estimation
| null | null | 3.25 | 3.75 |
Reject
|
5;4;3;3
|
2;2;2;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
safe imitation learning;inverse reinforcement learning
| null | 2.25 | null | null |
iclr
| 0 | 0.57735 | null |
main
| 3.5 |
3;3;3;5
|
3;2;2;3
| null |
Lagrangian Generative Adversarial Imitation Learning with Safety
| null | null | 2.5 | 4 |
Withdraw
|
3;4;5;4
|
2;3;2;2
|
null | null |
2022
| 1.75 | null | null | 0 | null | null | null |
1;2;2;2
| null | null | null |
Data-centric;semi-supervised learning
| null | 2.5 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
3;5;6;6
|
3;3;3;3
| null |
Data-centric Semi-supervised Learning
| null | null | 3 | 4 |
Withdraw
|
4;4;4;4
|
2;2;3;3
|
null |
New York University
|
2022
| 2.8 |
https://iclr.cc/virtual/2022/poster/6290; None
| null | 0 | null | null | null |
2;2;3;3;4
| null |
Aahlad Puli, Lily Zhang, Eric Oermann, Rajesh Ranganath
|
https://iclr.cc/virtual/2022/poster/6290
|
spurious correlations;out of distribution generalization;ml for health;representation learning
| null | 2.8 | null |
https://openreview.net/forum?id=12RoR2o32T
|
iclr
| -0.77407 | 0.989071 | null |
main
| 6.4 |
5;5;6;8;8
|
2;2;3;4;4
|
https://iclr.cc/virtual/2022/poster/6290
|
Out-of-distribution Generalization in the Presence of Nuisance-Induced Spurious Correlations
|
https://github.com/aahladpuli/Nuisance-Randomized-Distillation
| null | 3 | 3.6 |
Poster
|
5;4;3;3;3
|
2;3;3;2;4
|
null |
Columbia University, New York, NY 10027, USA; ETH Z¨urich, Z¨urich, Switzerland; The University of Texas at Austin, Austin, TX 78712, USA
|
2022
| 3.2 |
https://iclr.cc/virtual/2022/poster/7110; None
| null | 0 | null | null | null |
3;4;3;3;3
| null |
Kui Ren, Yunan Yang, Björn Engquist
|
https://iclr.cc/virtual/2022/poster/7110
|
weighted optimization;generalization error;feature regression;machine learning
| null | 1.4 | null |
https://openreview.net/forum?id=14F3fI6MGxX
|
iclr
| -0.408248 | -0.25 | null |
main
| 5.8 |
5;6;6;6;6
|
4;4;3;4;4
|
https://iclr.cc/virtual/2022/poster/7110
|
A Generalized Weighted Optimization Method for Computational Learning and Inversion
| null | null | 3.8 | 3.2 |
Poster
|
4;4;2;2;4
|
3;4;0;0;0
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
Metric Learning;Few-Shot Learning;Temporal Graph
| null | 2 | null | null |
iclr
| -0.57735 | 0.707107 | null |
main
| 4 |
3;3;5;5
|
3;2;3;4
| null |
Metric Learning on Temporal Graphs via Few-Shot Examples
| null | null | 3 | 3.25 |
Reject
|
3;4;3;3
|
2;2;2;2
|
null |
Noah’s Ark Lab, Huawei; College of Intelligence and Computing, Tianjin University; School of Computer Science and Engineering, Nanyang Technological University, Singapore
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/7013; None
| null | 0 | null | null | null |
3;2;3;3
| null |
Pengjie Gu, Mengchen Zhao, Jianye HAO, Bo An
|
https://iclr.cc/virtual/2022/poster/7013
|
coordination;reinforcement learning
| null | 3 | null |
https://openreview.net/forum?id=18Ys0-PzyPI
|
iclr
| 0.333333 | 0.57735 | null |
main
| 6.5 |
6;6;6;8
|
3;4;3;4
|
https://iclr.cc/virtual/2022/poster/7013
|
Online Ad Hoc Teamwork under Partial Observability
| null | null | 3.5 | 3.5 |
Poster
|
4;4;2;4
|
3;3;3;3
|
null | null |
2022
| 1.75 | null | null | 0 | null | null | null |
1;1;2;3
| null | null | null |
Conference Review;OpenReview;Gender;Bias;Fairness
| null | 2.25 | null | null |
iclr
| -0.980196 | 0.857493 | null |
main
| 4.5 |
1;5;6;6
|
2;3;4;3
| null |
An Investigation into the Role of Author Demographics in ICLR Participation and Review
| null | null | 3 | 4.25 |
Reject
|
5;4;4;4
|
1;2;3;3
|
null |
Mila, University of Montreal; Mila, University of Montreal, CIFAR Fellow
|
2022
| 3.25 |
https://iclr.cc/virtual/2022/poster/6503; None
| null | 0 | null | null | null |
2;3;4;4
| null |
Dinghuai Zhang, Jie Fu, Yoshua Bengio, Aaron Courville
|
https://iclr.cc/virtual/2022/poster/6503
|
biological sequence design;black-box optimization;likelihood-free inference;Bayesian inference
| null | 1.75 | null |
https://openreview.net/forum?id=1HxTO6CTkz
|
iclr
| -0.174078 | 0.522233 | null |
main
| 7.5 |
6;6;8;10
|
3;4;4;4
|
https://iclr.cc/virtual/2022/poster/6503
|
Unifying Likelihood-free Inference with Black-box Optimization and Beyond
| null | null | 3.75 | 3.75 |
Spotlight
|
4;4;3;4
|
2;0;2;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;3;2
| null | null | null | null | null | 2.5 | null | null |
iclr
| 0 | 0.973329 | null |
main
| 4.75 |
3;5;5;6
|
2;3;3;4
| null |
ImaginE: An Imagination-Based Automatic Evaluation Metric for Natural Language Generation
| null | null | 3 | 4 |
Withdraw
|
4;4;4;4
|
2;2;3;3
|
null |
MPI for Intelligent Systems, Tübingen; School of Informatics, University of Edinburgh
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6285; None
| null | 0 | null | null | null |
3;3;3;3;3
| null |
Cian Eastwood, Ian Mason, Chris Williams, Bernhard Schoelkopf
|
https://iclr.cc/virtual/2022/poster/6285
|
Transfer learning;dataset shift;unsupervised domain adaptation;source-free domain adaptation
| null | 3.2 | null |
https://openreview.net/forum?id=1JDiK_TbV4S
|
iclr
| 0.25 | 1 | null |
main
| 7.6 |
6;8;8;8;8
|
2;4;4;4;4
|
https://iclr.cc/virtual/2022/poster/6285
|
Source-Free Adaptation to Measurement Shift via Bottom-Up Feature Restoration
| null | null | 3.6 | 4.2 |
Spotlight
|
4;4;4;4;5
|
3;3;3;4;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
3;3;3;2
| null | null | null |
disentanglement representations;multi-task learning
| null | 3 | null | null |
iclr
| -1 | 0.57735 | null |
main
| 5.5 |
5;5;6;6
|
2;3;3;3
| null |
On the relationship between disentanglement and multi-task learning
| null | null | 2.75 | 3.5 |
Reject
|
4;4;3;3
|
2;3;4;3
|
null |
LIRIS, INSA Lyon, France; Naver Labs Europe, France; Simon Fraser Univ., Canada; LAGEPP, Univ. Lyon 1, France; Meta AI
|
2022
| 3.333333 |
https://iclr.cc/virtual/2022/poster/6541; None
| null | 0 | null | null | null |
3;3;4
| null |
Steeven Janny, Fabien Baradel, Natalia Neverova, Madiha Nadri, Greg Mori, Christian Wolf
|
https://iclr.cc/virtual/2022/poster/6541
| null | null | 3.666667 | null |
https://openreview.net/forum?id=1L0C5ROtFp
|
iclr
| -0.866025 | 0 | null |
main
| 8.666667 |
8;8;10
|
4;4;4
|
https://iclr.cc/virtual/2022/poster/6541
|
Filtered-CoPhy: Unsupervised Learning of Counterfactual Physics in Pixel Space
| null | null | 4 | 4 |
Oral
|
4;5;3
|
3;4;4
|
null | null |
2022
| 1.75 | null | null | 0 | null | null | null |
1;2;2;2
| null | null | null |
network calibration;temperature scaling;Expected Calibration Error (ECE)
| null | 2 | null | null |
iclr
| 0 | 0 | null |
main
| 3 |
3;3;3;3
|
3;2;3;3
| null |
Network calibration by weight scaling
| null | null | 2.75 | 4 |
Withdraw
|
4;5;4;3
|
2;2;2;2
|
null |
Massachusetts Institute of Technology
|
2022
| 3.25 |
https://iclr.cc/virtual/2022/poster/6636; None
| null | 0 | null | null | null |
4;2;4;3
| null |
Sugandha Sharma, Aidan Curtis, Marta Kryven, Joshua B Tenenbaum, Ila Fiete
|
https://iclr.cc/virtual/2022/poster/6636
|
Cognitive Science;Bayesian Framework;Program Induction;Spatial Navigation;Planning;Map Learning
| null | 3.25 | null |
https://openreview.net/forum?id=1NUsBU-7HAL
|
iclr
| 0.57735 | 0 | null |
main
| 6.5 |
6;6;6;8
|
3;3;3;3
|
https://iclr.cc/virtual/2022/poster/6636
|
Map Induction: Compositional spatial submap learning for efficient exploration in novel environments
| null | null | 3 | 3.5 |
Poster
|
3;4;3;4
|
4;3;2;4
|
null |
Harvard University, Cambridge, MA 02138, USA
|
2022
| 3.333333 |
https://iclr.cc/virtual/2022/poster/7005; None
| null | 0 | null | null | null |
3;4;3
| null |
Alexander Atanasov, Blake Bordelon, Cengiz Pehlevan
|
https://iclr.cc/virtual/2022/poster/7005
|
Neural Tangent Kernel;Feature Learning;Inductive Bias of Neural Networks
| null | 3 | null |
https://openreview.net/forum?id=1NvflqAdoom
|
iclr
| -0.944911 | 0.188982 | null |
main
| 6.333333 |
5;6;8
|
4;2;4
|
https://iclr.cc/virtual/2022/poster/7005
|
Neural Networks as Kernel Learners: The Silent Alignment Effect
| null | null | 3.333333 | 3.666667 |
Poster
|
4;4;3
|
3;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;2;3
| null | null | null |
domain generalization;semantic segmentation;test-time training
| null | 2.5 | null | null |
iclr
| -0.333333 | 0 | null |
main
| 5.25 |
5;5;5;6
|
4;3;2;3
| null |
Adaptive Generalization for Semantic Segmentation
| null | null | 3 | 3.25 |
Reject
|
4;3;3;3
|
2;3;2;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;3;2
| null | null | null | null | null | 2.5 | null | null |
iclr
| -0.57735 | 1 | null |
main
| 5.25 |
5;5;5;6
|
3;3;3;4
| null |
FedNAS: Federated Deep Learning via Neural Architecture Search
| null | null | 3.25 | 3.5 |
Reject
|
4;4;3;3
|
2;3;2;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
3;2;4;2
| null | null | null |
genome assembly;graph neural networks;assembly graph;path finding
| null | 2 | null | null |
iclr
| -0.229416 | 0 | null |
main
| 4 |
3;3;5;5
|
4;2;3;3
| null |
Genome Sequence Reconstruction Using Gated Graph Convolutional Network
| null | null | 3 | 3.75 |
Reject
|
4;4;2;5
|
1;3;2;2
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
energy-based models;generative modeling;neural networks;duality;Fenchel;maximum mean discrepancy;maximum likelihood;active;lazy;score matching;measure;feature
| null | 1.5 | null | null |
iclr
| 0.132453 | 0.688247 | null |
main
| 4.75 |
3;5;5;6
|
3;4;3;4
| null |
Dual Training of Energy-Based Models with Overparametrized Shallow Neural Networks
| null | null | 3.5 | 3.25 |
Reject
|
3;4;3;3
|
1;1;2;2
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
3;3;3;2
| null | null | null |
Diversity;Metric;Random Network Distillation;Generative
| null | 2 | null | null |
iclr
| 0 | 0.174078 | null |
main
| 3.5 |
3;3;3;5
|
4;2;2;3
| null |
A Flexible Measurement of Diversity in Datasets with Random Network Distillation
| null | null | 2.75 | 4 |
Withdraw
|
4;5;3;4
|
3;1;2;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
1;1;3;3
| null | null | null |
Deep Learning;Recurrent Neural Networks;Exploding Gradient Problem;Deep Learning Generalization;Orthogonal RNNs
| null | 1.75 | null | null |
iclr
| 0.555556 | -0.19245 | null |
main
| 4.25 |
3;3;5;6
|
3;4;4;3
| null |
SGORNN: Combining Scalar Gates and Orthogonal Constraints in Recurrent Networks
| null | null | 3.5 | 3.75 |
Reject
|
4;3;4;4
|
1;1;2;3
|
null |
Google Research, Brain Team; University of Toronto
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/6250; None
| null | 0 | null | null | null |
3;2;2;3
| null |
Danijar Hafner
|
https://iclr.cc/virtual/2022/poster/6250
|
Evaluation;Reinforcement Learning;Environment;Benchmark;Unsupervised Reinforcement Learning;Exploration
| null | 1.5 | null |
https://openreview.net/forum?id=1W0z96MFEoH
|
iclr
| 0 | 0 | null |
main
| 6 |
5;5;6;8
|
4;4;3;4
|
https://iclr.cc/virtual/2022/poster/6250
|
Benchmarking the Spectrum of Agent Capabilities
| null | null | 3.75 | 4 |
Poster
|
4;4;4;4
|
2;2;2;0
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
Classification;Normalization
| null | 2.25 | null | null |
iclr
| -0.229416 | 0 | null |
main
| 4.75 |
3;5;5;6
|
3;4;2;3
| null |
BWCP: Probabilistic Learning-to-Prune Channels for ConvNets via Batch Whitening
| null | null | 3 | 4.5 |
Reject
|
5;4;4;5
|
1;3;2;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
3;1;2;2
| null | null | null |
imitation learning;language;planning
| null | 2.25 | null | null |
iclr
| -0.57735 | 0.333333 | null |
main
| 5.25 |
5;5;5;6
|
2;3;3;3
| null |
Improving Long-Horizon Imitation Through Language Prediction
|
<github will be made public after reviewing period>
| null | 2.75 | 4.5 |
Reject
|
4;5;5;4
|
1;2;3;3
|
null |
Paper under double-blind review
|
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;3;2
| null | null | null | null | null | 0 | null | null |
iclr
| 0.418121 | -0.83205 | null |
main
| 5.5 |
3;5;6;8
|
4;4;3;3
| null |
On the Global Convergence of Gradient Descent for multi-layer ResNets in the mean-field regime
| null | null | 3.5 | 3.75 |
Reject
|
4;3;3;5
| null |
null | null |
2022
| 2.8 | null | null | 0 | null | null | null |
2;2;4;3;3
| null | null | null |
autoregressive generative model;exposure bias;energy-based model
| null | 2.6 | null | null |
iclr
| 0.179029 | 0 | null |
main
| 5 |
3;5;5;6;6
|
3;3;3;3;3
| null |
YOUR AUTOREGRESSIVE GENERATIVE MODEL CAN BE BETTER IF YOU TREAT IT AS AN ENERGY-BASED ONE
| null | null | 3 | 3.6 |
Reject
|
4;2;3;4;5
|
1;3;3;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
meta-learning;uncertainty estimation
| null | 1.75 | null | null |
iclr
| -0.57735 | 0.57735 | null |
main
| 2.5 |
1;3;3;3
|
2;3;3;2
| null |
Amortized Posterior on Latent Variables in Gaussian Process
| null | null | 2.5 | 3.5 |
Withdraw
|
4;3;3;4
|
0;2;3;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
1;3;3;2
| null | null | null |
Edit;Representation Learning;Source-code;natural language editing
| null | 2.5 | null | null |
iclr
| 0.333333 | -1 | null |
main
| 4.5 |
3;5;5;5
|
3;2;2;2
| null |
Learning to Model Editing Processes
| null | null | 2.25 | 4.25 |
Reject
|
4;4;4;5
|
2;3;2;3
|
null | null |
2022
| 2.2 | null | null | 0 | null | null | null |
2;2;2;3;2
| null | null | null |
representation learning;representational similarity;distributed representations
| null | 2.4 | null | null |
iclr
| -0.361158 | 0.361158 | null |
main
| 4.6 |
3;3;5;6;6
|
2;4;2;4;4
| null |
Dominant Datapoints and the Block Structure Phenomenon in Neural Network Hidden Representations
| null | null | 3.2 | 3.4 |
Reject
|
3;4;4;3;3
|
2;2;3;3;2
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
multi-modal learning
| null | 1.5 | null | null |
iclr
| -0.555556 | 0 | null |
main
| 4.25 |
3;3;5;6
|
2;4;3;3
| null |
Modality Laziness: Everybody's Business is Nobody's Business
| null | null | 3 | 3.25 |
Withdraw
|
4;3;3;3
|
1;2;3;0
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
1;2;2;4
| null | null | null |
Language Models;Pre-training;Logical Reasoning;Natural Language Understanding
| null | 2.25 | null | null |
iclr
| -1 | 1 | null |
main
| 4 |
3;3;5;5
|
2;2;3;3
| null |
Logic Pre-Training of Language Models
| null | null | 2.5 | 4.5 |
Reject
|
5;5;4;4
|
2;2;2;3
|
null | null |
2022
| 1.75 | null | null | 0 | null | null | null |
1;1;2;3
| null | null | null |
adversarial robustness;differential privacy;adversarial training;calibration;deep learning
| null | 1.25 | null | null |
iclr
| 0.522233 | 0.774597 | null |
main
| 3.5 |
3;3;3;5
|
2;1;3;4
| null |
Practical Adversarial Training with Differential Privacy for Deep Learning
| null | null | 2.5 | 4.25 |
Withdraw
|
4;5;3;5
|
0;1;1;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
Deep Learning;Adversarial Perturbation;Adversarial Example;Categorical Learning
| null | 1.75 | null | null |
iclr
| 0 | 0 | null |
main
| 3 |
3;3;3;3
|
3;2;2;2
| null |
Neural Networks Playing Dough: Investigating Deep Cognition With a Gradient-Based Adversarial Attack
| null | null | 2.25 | 3.75 |
Reject
|
4;5;2;4
|
2;2;1;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
Interpretable Reinforcement Learning;Generalization;Robustness
| null | 2 | null | null |
iclr
| -0.333333 | -0.57735 | null |
main
| 4.5 |
3;5;5;5
|
4;3;4;3
| null |
Learning Two-Step Hybrid Policy for Graph-Based Interpretable Reinforcement Learning
| null | null | 3.5 | 3.75 |
Reject
|
4;3;4;4
|
2;3;3;0
|
null |
Paper under double-blind review
|
2022
| 2.333333 | null | null | 0 | null | null | null |
2;2;3
| null | null | null |
coreset;clustering;kernel;PTAS;streaming;spectral clustering;k-means
| null | 3 | null | null |
iclr
| 0 | 0 | null |
main
| 5.333333 |
3;5;8
|
4;4;4
| null |
Coresets for Kernel Clustering
| null | null | 4 | 4 |
Reject
|
4;4;4
|
3;3;3
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;2;3
| null | null | null |
Self-Learning;Domain Adaptation;Robustness;Pseudolabeling;Entropy Minimization;Corruption Robustness
| null | 3 | null | null |
iclr
| -0.944911 | 0 | null |
main
| 6.333333 |
5;6;8
|
3;3;3
| null |
If your data distribution shifts, use self-learning
| null | null | 3 | 3.666667 |
Reject
|
4;4;3
|
2;3;4
|
null |
Under double-blind review
|
2022
| 1 | null | null | 0 | null | null | null |
1;1;1
| null | null | null |
COVID-19;Machine learning;Classification
| null | 1.666667 | null | null |
iclr
| 0 | -0.5 | null |
main
| 1.666667 |
1;1;3
|
2;3;2
| null |
Machine Learning Applications in Forecasting of COVID-19 Based on Patients' Individual Symptoms
| null | null | 2.333333 | 5 |
Withdraw
|
5;5;5
|
1;2;2
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;3;2
| null | null | null | null | null | 1.75 | null | null |
iclr
| 0.57735 | 0.333333 | null |
main
| 5.25 |
5;5;5;6
|
3;2;3;3
| null |
Training Meta-Surrogate Model for Transferable Adversarial Attack
| null | null | 2.75 | 4 |
Withdraw
|
5;3;3;5
|
2;2;3;0
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
neural network learning;nonparametric methods;convex optimization
| null | 2.5 | null | null |
iclr
| -0.471405 | 0.942809 | null |
main
| 5 |
3;5;6;6
|
3;4;4;4
| null |
Nonparametric Learning of Two-Layer ReLU Residual Units
| null | null | 3.75 | 3.75 |
Reject
|
4;4;3;4
|
2;2;3;3
|
null |
Amazon.com
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/7094; None
| null | 0 | null | null | null |
4;3;3;2
| null |
Wenqing Zheng, Edward Huang, Nikhil Rao, Sumeet Katariya, Zhangyang Wang, Karthik Subbian
|
https://iclr.cc/virtual/2022/poster/7094
|
Graph Neural Networks;Cold Start;Knowledge Distillation
| null | 1.75 | null |
https://openreview.net/forum?id=1ugNpm7W6E
|
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6;6
|
3;4;3;3
|
https://iclr.cc/virtual/2022/poster/7094
|
Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods
|
https://github.com/amazon-research/gnn-tail-generalization
| null | 3.25 | 3.5 |
Poster
|
3;4;3;4
|
0;2;3;2
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
3;2;3;3
| null | null | null |
Score-based Diffusion Model;Normalizing Flow Model;Variational Inference;Variational Gap;Stochastic Calculus
| null | 2.5 | null | null |
iclr
| -0.57735 | -1 | null |
main
| 5.5 |
5;5;6;6
|
4;4;3;3
| null |
Maximum Likelihood Training of Parametrized Diffusion Model
| null | null | 3.5 | 3.75 |
Reject
|
4;4;4;3
|
3;2;2;3
|
null |
DeepMind, London
|
2022
| 2.25 |
https://iclr.cc/virtual/2022/poster/5968; None
| null | 0 | null | null | null |
2;2;3;2
| null |
Jonathan Godwin, Michael Schaarschmidt, Alexander Gaunt, Alvaro Sanchez Gonzalez, Yulia Rubanova, Petar Veličković, James Kirkpatrick, Peter Battaglia
|
https://iclr.cc/virtual/2022/poster/5968
|
Graph Neural Networks;GNNs;Deep Learning;Molecular Property Prediction
| null | 2 | null |
https://openreview.net/forum?id=1wVvweK3oIb
|
iclr
| -1 | 0.57735 | null |
main
| 6.5 |
6;6;6;8
|
3;3;4;4
|
https://iclr.cc/virtual/2022/poster/5968
|
Simple GNN Regularisation for 3D Molecular Property Prediction and Beyond
| null | null | 3.5 | 3.5 |
Poster
|
4;4;4;2
|
2;3;0;3
|
null | null |
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6307; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Tom Joy, Yuge Shi, Philip Torr, Tom Rainforth, Sebastian Schmon, Siddharth N
|
https://iclr.cc/virtual/2022/poster/6307
|
Multimodal Variational Autoencoder;Variational Autoencoder
| null | 2.5 | null |
https://openreview.net/forum?id=1xXvPrAshao
|
iclr
| 0.345857 | 0.132453 | null |
main
| 6.25 |
5;6;6;8
|
4;4;3;4
|
https://iclr.cc/virtual/2022/poster/6307
|
Learning Multimodal VAEs through Mutual Supervision
| null | null | 3.75 | 3.75 |
Spotlight
|
3;3;5;4
|
2;3;3;2
|
null | null |
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6902; None
| null | 0 | null | null | null |
3;3;2;3
| null |
Kamil Ciosek
|
https://iclr.cc/virtual/2022/poster/6902
|
reinforcement learning;imitation learning;Markov Decision Process;continuous control
| null | 2.25 | null |
https://openreview.net/forum?id=1zwleytEpYx
|
iclr
| -0.333333 | -0.57735 | null |
main
| 5.75 |
5;6;6;6
|
4;3;4;3
|
https://iclr.cc/virtual/2022/poster/6902
|
Imitation Learning by Reinforcement Learning
| null | null | 3.5 | 3.75 |
Poster
|
4;4;3;4
|
2;2;2;3
|
null | null |
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6332; None
| null | 0 | null | null | null |
3;4;3;2
| null |
Uiwon Hwang, Heeseung Kim, Dahuin Jung, Hyemi Jang, Hyungyu Lee, Sungroh Yoon
|
https://iclr.cc/virtual/2022/poster/6332
|
Generative Adversarial Networks;Unsupervised Conditional GANs
| null | 2.75 | null |
https://openreview.net/forum?id=2-mkiUs9Jx7
|
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6;6
|
4;3;4;3
|
https://iclr.cc/virtual/2022/poster/6332
|
Stein Latent Optimization for Generative Adversarial Networks
| null | null | 3.5 | 3.5 |
Poster
|
3;4;3;4
|
3;3;3;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
1;2;2;3
| null | null | null |
tabular data;DL alternative;architecture
| null | 1.75 | null | null |
iclr
| -0.774597 | 0 | null |
main
| 4 |
1;5;5;5
|
3;3;3;3
| null |
Sparse Hierarchical Table Ensemble
| null | null | 3 | 3.5 |
Reject
|
5;4;3;2
|
1;2;2;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
manifold;geometry;graph embedding;geodesic;differential equations;BVP;differentiable programming
| null | 2.25 | null | null |
iclr
| 0.396059 | 0.886621 | null |
main
| 3.25 |
1;3;3;6
|
2;3;2;4
| null |
Learning Complex Geometric Structures from Data with Deep Riemannian Manifolds
| null | null | 2.75 | 3 |
Withdraw
|
2;3;4;3
|
1;2;3;3
|
null | null |
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6977; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Pierre-Alexandre Kamienny, Jean Tarbouriech, sylvain lamprier, Alessandro Lazaric, Ludovic Denoyer
|
https://iclr.cc/virtual/2022/poster/6977
|
unsupervised reinforcement learning;skill discovery;mutual information
| null | 3 | null |
https://openreview.net/forum?id=25kzAhUB1lz
|
iclr
| -0.57735 | 1 | null |
main
| 7 |
6;6;8;8
|
3;3;4;4
|
https://iclr.cc/virtual/2022/poster/6977
|
Direct then Diffuse: Incremental Unsupervised Skill Discovery for State Covering and Goal Reaching
| null | null | 3.5 | 3.75 |
Poster
|
4;4;4;3
|
3;3;3;3
|
null | null |
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6100; None
| null | 0 | null | null | null |
2;3;4;3
| null |
Shangyuan Tong, Timur Garipov, Yang Zhang, Shiyu Chang, Tommi Jaakkola
|
https://iclr.cc/virtual/2022/poster/6100
|
support alignment;distribution alignment;optimal transport;domain adaptation
| null | 2.75 | null |
https://openreview.net/forum?id=26gKg6x-ie
|
iclr
| 0.57735 | 0.57735 | null |
main
| 6.75 |
3;8;8;8
|
3;4;3;4
|
https://iclr.cc/virtual/2022/poster/6100
|
Adversarial Support Alignment
| null | null | 3.5 | 3.5 |
Spotlight
|
3;4;4;3
|
2;3;3;3
|
null |
Under double-blind review
|
2022
| 1.75 | null | null | 0 | null | null | null |
1;2;2;2
| null | null | null |
Wargame;Reinforcement learning;Multiple attribute decision making;Intelligent game
| null | 1 | null | null |
iclr
| -0.870388 | 1 | null |
main
| 2.5 |
1;1;3;5
|
1;1;2;3
| null |
$$Research on fusion algorithm of multi-attribute decision making and reinforcement learning based on intuitionistic fuzzy number in wargame environment$$
| null | null | 1.75 | 3.5 |
Reject
|
4;4;4;2
|
1;2;1;0
|
null |
Department of Electrical and Computer Engineering, Rice University
|
2022
| 3.25 |
https://iclr.cc/virtual/2022/poster/6624; None
| null | 0 | null | null | null |
3;3;4;3
| null |
Yonggan Fu, Shunyao Zhang, Shang Wu, Cheng Wan, Yingyan Lin
|
https://iclr.cc/virtual/2022/poster/6624
|
Vision transformer;adversarial examples;robustness
| null | 3 | null |
https://openreview.net/forum?id=28ib9tf6zhr
|
iclr
| 0.57735 | 0.57735 | null |
main
| 7 |
6;6;8;8
|
3;4;4;4
|
https://iclr.cc/virtual/2022/poster/6624
|
Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?
|
https://github.com/RICE-EIC/Patch-Fool
| null | 3.75 | 3.75 |
Poster
|
4;3;4;4
|
2;3;4;3
|
null | null |
2022
| 1.25 | null | null | 0 | null | null | null |
1;1;2;1
| null | null | null |
Neural Architecture Search;Hardware-Aware;Predictors;Deep Learning
| null | 2.75 | null | null |
iclr
| 0.927173 | -0.333333 | null |
main
| 5.75 |
5;6;6;6
|
4;3;4;4
| null |
What to expect of hardware metric predictors in NAS
| null | null | 3.75 | 3.75 |
Reject
|
2;4;5;4
|
2;4;3;2
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
3;3;2;3
| null | null | null |
low-capacity model;large-scale prediction;efficient inference;hybrid networks;routing nets;coverage and latency;FLOPs
| null | 2.5 | null | null |
iclr
| 0.333333 | 0 | null |
main
| 5.25 |
5;5;5;6
|
3;3;3;3
| null |
Hybrid Cloud-Edge Networks for Efficient Inference
| null | null | 3 | 3.75 |
Reject
|
3;4;4;4
|
3;2;2;3
|
null | null |
2022
| 1.666667 | null | null | 0 | null | null | null |
1;2;2
| null | null | null |
catastrophic forgetting;incremental similarity learning
| null | 0.666667 | null | null |
iclr
| -0.5 | 1 | null |
main
| 2.333333 |
1;1;5
|
2;2;3
| null |
ConVAEr: Convolutional Variational AutoEncodeRs for incremental similarity learning
| null | null | 2.333333 | 3.333333 |
Reject
|
4;3;3
|
1;1;0
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
1;2;3
| null | null | null |
Generalization bounds;deep neural networks;stability
| null | 2 | null | null |
iclr
| -0.917663 | 0.802955 | null |
main
| 5.333333 |
3;5;8
|
2;4;4
| null |
Stability analysis of SGD through the normalized loss function
| null | null | 3.333333 | 3.666667 |
Reject
|
4;4;3
|
1;2;3
|
null | null |
2022
| 1.333333 | null | null | 0 | null | null | null |
1;2;1
| null | null | null |
Graph Neural Networks;Distribution Shifts;Out-of-Distribution Generalization
| null | 2.666667 | null | null |
iclr
| 0 | 0 | null |
main
| 3 |
3;3;3
|
3;2;3
| null |
A Closer Look at Distribution Shifts and Out-of-Distribution Generalization on Graphs
| null | null | 2.666667 | 4.333333 |
Withdraw
|
5;4;4
|
2;3;3
|
null | null |
2022
| 1.666667 | null | null | 0 | null | null | null |
1;1;3
| null | null | null |
GANs;Generative adversarial networks;Contrastive learning;Conditional image generation
| null | 2 | null | null |
iclr
| 0 | 0.866025 |
https://anonymous.4open.science/r/InfoSCC-GAN-D113
|
main
| 3 |
1;3;5
|
2;2;3
| null |
Information-theoretic stochastic contrastive conditional GAN: InfoSCC-GAN
| null | null | 2.333333 | 4 |
Reject
|
4;4;4
|
1;2;3
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
2;3;3
| null | null | null |
Bayesian optimization;hyperparameter optimization;automatic termination
| null | 2.666667 | null | null |
iclr
| -0.5 | -0.5 | null |
main
| 5.666667 |
5;6;6
|
3;3;2
| null |
Automatic Termination for Hyperparameter Optimization
| null | null | 2.666667 | 3.666667 |
Reject
|
4;3;4
|
2;3;3
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
3;2;3
| null | null | null |
nonconvex optimization;Langevin based algorithm
| null | 1.666667 | null | null |
iclr
| -0.5 | 1 | null |
main
| 6 |
5;5;8
|
3;3;4
| null |
Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks
| null | null | 3.333333 | 3.333333 |
Withdraw
|
3;4;3
|
2;0;3
|
null | null |
2022
| 1.75 | null | null | 0 | null | null | null |
2;1;2;2
| null | null | null |
Graph Neural Network;Attention;Scalability
| null | 2.5 | null | null |
iclr
| -0.333333 | -0.57735 | null |
main
| 5.25 |
3;6;6;6
|
4;4;3;3
| null |
Graph Attention Multi-layer Perceptron
| null | null | 3.5 | 3.75 |
Reject
|
4;4;3;4
|
2;3;2;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null | null | null | 2.25 | null | null |
iclr
| 0 | -0.57735 | null |
main
| 3.5 |
3;3;3;5
|
3;3;2;2
| null |
KINet: Keypoint Interaction Networks for Unsupervised Forward Modeling
| null | null | 2.5 | 4 |
Reject
|
4;4;4;4
|
2;2;2;3
|
null | null |
2022
| 1.5 | null | null | 0 | null | null | null |
1;2;1;2
| null | null | null |
out-of-distribution generalization;domain generalization;pre-training
| null | 2.25 | null | null |
iclr
| -0.789474 | 0.927173 | null |
main
| 4.75 |
3;5;5;6
|
2;3;3;3
| null |
An Empirical Study of Pre-trained Models on Out-of-distribution Generalization
| null | null | 2.75 | 3.25 |
Reject
|
5;3;2;3
|
2;2;2;3
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;3;3;3
| null | null | null |
Backdoor Attack;Data Poisoning;Noisy Label
| null | 2.5 | null | null |
iclr
| -0.132453 | 0 | null |
main
| 4.75 |
3;5;5;6
|
3;2;4;3
| null |
Defending Backdoor Data Poisoning Attacks by Using Noisy Label Defense Algorithm
| null | null | 3 | 3.75 |
Reject
|
4;3;4;4
|
2;2;3;3
|
null |
Laboratory for Information and Inference Systems (LIONS), EPFL; Department of Electrical Engineering (ESAT-STADIUS), KU Leuven; Laboratoire Traitement et Communication d’Information, Télécom Paris, Institut Polytechnique de Paris; Not provided in the text
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6528; None
| null | 0 | null | null | null |
2;3;3;4
| null |
Thomas Pethick "3026 Puya Latafat "3026 Panagiotis Patrinos[2] "3026 Olivier Fercoq "3026 Volkan Cevher[1]
|
https://iclr.cc/virtual/2022/poster/6528
|
Minimax;Nonconvex-Nonconcave;Variational inequilities;Saddle point problem;First-order methods;Limit cycles
| null | 2.25 | null |
https://openreview.net/forum?id=2_vhkAMARk
|
iclr
| 0.333333 | 0 | null |
main
| 7.25 |
5;8;8;8
|
4;4;4;4
|
https://iclr.cc/virtual/2022/poster/6528
|
Escaping limit cycles: Global convergence for constrained nonconvex-nonconcave minimax problems
| null | null | 4 | 3.25 |
Spotlight
|
3;3;3;4
|
0;3;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;1;3
| null | null | null |
fairness;bias;long tailed learning;imbalanced learning
| null | 2.5 | null | null |
iclr
| 0.493742 | 0.994558 | null |
main
| 4.75 |
3;3;5;8
|
2;2;3;4
| null |
Where is the bottleneck in long-tailed classification?
| null | null | 2.75 | 4.75 |
Reject
|
5;4;5;5
|
2;2;2;4
|
null |
Carnegie Mellon University, Determined AI; Carnegie Mellon University; ENS PSL University
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/6249; None
| null | 0 | null | null | null |
2;3;2;3
| null |
Lucio Dery, Paul Michel, Ameet Talwalkar, Graham Neubig
|
https://iclr.cc/virtual/2022/poster/6249
|
pre-training;multitask learning;meta-learning;deeplearning;end-task aware training;NLP
| null | 2.5 | null |
https://openreview.net/forum?id=2bO2x8NAIMB
|
iclr
| -0.57735 | 0.333333 | null |
main
| 5.75 |
5;6;6;6
|
3;3;3;4
|
https://iclr.cc/virtual/2022/poster/6249
|
Should We Be Pre-training? An Argument for End-task Aware Training as an Alternative
| null | null | 3.25 | 3.5 |
Poster
|
4;3;4;3
|
2;2;3;3
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;3;3;3
| null | null | null |
multiple instance learning;active learning
| null | 2.75 | null | null |
iclr
| -0.57735 | 0.174078 | null |
main
| 3.75 |
3;3;3;6
|
2;2;4;3
| null |
Active Deep Multiple Instance Learning
| null | null | 2.75 | 4 |
Withdraw
|
3;5;5;3
|
2;3;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
Interpretable machine learning;XAI;Uncertainty;Prototype-based classification
| null | 2.25 | null | null |
iclr
| 0.080845 | 0.886621 | null |
main
| 5.25 |
3;5;5;8
|
2;3;2;4
| null |
Beyond Examples: Constructing Explanation Space for Explaining Prototypes
| null | null | 2.75 | 2.75 |
Reject
|
3;3;2;3
|
2;2;2;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null | null | null | 2.25 | null | null |
iclr
| 0.246183 | 0.471405 | null |
main
| 5 |
3;5;6;6
|
3;3;4;3
| null |
Sequential Covariate Shift Detection Using Classifier Two-Sample Tests
| null | null | 3.25 | 3.75 |
Reject
|
3;5;3;4
|
3;0;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2
| null | null | null |
ES;ENAS;hybrid;search;space;blackbox;combinatorial;optimization;reinforcement;learning;mujoco;policies;evolutionary;computation;neuroevolution;high;dimension;supernet;one-shot;nas;neural;architecture;search;efficient
| null | 2.333333 | null | null |
iclr
| -0.5 | 0 | null |
main
| 3.666667 |
3;3;5
|
3;3;3
| null |
ES-ENAS: Blackbox Optimization over Hybrid Spaces via Combinatorial and Continuous Evolution
| null | null | 3 | 3.333333 |
Withdraw
|
4;3;3
|
2;2;3
|
null |
Huawei Kirin Solution; RALI & Mila, Université de Montréal, Canada CIFAR AI Chair; Department of Electrical and Computer Engineering, University of Alberta
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/7053; None
| null | 0 | null | null | null |
3;3;3
| null |
Shengyao Lu, Bang Liu, Keith G Mills, SHANGLING JUI, Di Niu
|
https://iclr.cc/virtual/2022/poster/7053
|
systematicity;graph reasoning
| null | 3 | null |
https://openreview.net/forum?id=2eXhNpHeW6E
|
iclr
| 0.5 | 0.5 | null |
main
| 5.666667 |
5;6;6
|
3;4;3
|
https://iclr.cc/virtual/2022/poster/7053
|
R5: Rule Discovery with Reinforced and Recurrent Relational Reasoning
| null | null | 3.333333 | 3.666667 |
Spotlight
|
3;5;3
|
3;3;3
|
null |
MIT Center for Theoretical Physics, Cambridge, MA 02139, USA
|
2022
| 3.666667 |
https://iclr.cc/virtual/2022/poster/6777; None
| null | 0 | null | null | null |
3;4;4
| null |
Eric Anschuetz
|
https://iclr.cc/virtual/2022/poster/6777
|
loss landscapes;quantum;Wishart spin-glass model
| null | 2.333333 | null |
https://openreview.net/forum?id=2f1z55GVQN
|
iclr
| -1 | 1 | null |
main
| 7.333333 |
6;8;8
|
2;4;4
|
https://iclr.cc/virtual/2022/poster/6777
|
Critical Points in Quantum Generative Models
| null | null | 3.333333 | 3.333333 |
Poster
|
4;3;3
|
2;3;2
|
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