pdf
stringlengths 49
199
⌀ | aff
stringlengths 1
1.36k
⌀ | year
stringclasses 19
values | technical_novelty_avg
float64 0
4
⌀ | video
stringlengths 21
47
⌀ | doi
stringlengths 31
63
⌀ | presentation_avg
float64 0
4
⌀ | proceeding
stringlengths 43
129
⌀ | presentation
stringclasses 796
values | sess
stringclasses 576
values | technical_novelty
stringclasses 700
values | arxiv
stringlengths 10
16
⌀ | author
stringlengths 1
1.96k
⌀ | site
stringlengths 37
191
⌀ | keywords
stringlengths 2
582
⌀ | oa
stringlengths 86
198
⌀ | empirical_novelty_avg
float64 0
4
⌀ | poster
stringlengths 57
95
⌀ | openreview
stringlengths 41
45
⌀ | conference
stringclasses 11
values | corr_rating_confidence
float64 -1
1
⌀ | corr_rating_correctness
float64 -1
1
⌀ | project
stringlengths 1
162
⌀ | track
stringclasses 3
values | rating_avg
float64 0
10
⌀ | rating
stringlengths 1
17
⌀ | correctness
stringclasses 809
values | slides
stringlengths 32
41
⌀ | title
stringlengths 2
192
⌀ | github
stringlengths 3
165
⌀ | authors
stringlengths 7
161
⌀ | correctness_avg
float64 0
5
⌀ | confidence_avg
float64 0
5
⌀ | status
stringclasses 22
values | confidence
stringlengths 1
17
⌀ | empirical_novelty
stringclasses 763
values |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
null |
Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, CA 94720, USA
|
2017
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Deep learning;Theory
| null | 0 | null | null |
iclr
| -1 | 0 | null |
main
| 4.333333 |
4;4;5
| null | null |
Rotation Plane Doubly Orthogonal Recurrent Neural Networks
| null | null | 0 | 3.666667 |
Reject
|
4;4;3
| null |
null |
Department of Computer Science, ETH Zürich, Switzerland
|
2017
| 0 | null | null | 0 | null | null | null | null | null | null | null | null | null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 7 |
5;8;8
| null | null |
Program Synthesis for Character Level Language Modeling
| null | null | 0 | 3 |
Poster
|
3;2;4
| null |
null |
Universit ´e Cˆote dAzur & CNRS, I3S, France
|
2017
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Deep learning;Supervised Learning;Optimization
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6
| null | null |
Introducing Active Learning for CNN under the light of Variational Inference
| null | null | 0 | 1.666667 |
Reject
|
2;2;1
| null |
null |
Institute of Bioinformatics, Johannes Kepler University, Linz, Austria
|
2017
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Deep learning;Unsupervised Learning;Applications
| null | 0 | null | null |
iclr
| -1 | 0 | null |
main
| 4.666667 |
4;5;5
| null | null |
Rectified Factor Networks for Biclustering
| null | null | 0 | 2.666667 |
Reject
|
4;2;2
| null |
null |
Computer Vision and Systems Laboratory, Department of Electrical Engineering and Computer Engineering, Universitè Laval, Quèbec, QC G1V 0A6, Canada
|
2017
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Deep learning;Computer vision;Optimization
| null | 0 | null | null |
iclr
| 0.454545 | 0 | null |
main
| 6.25 |
5;6;7;7
| null | null |
Alternating Direction Method of Multipliers for Sparse Convolutional Neural Networks
| null | null | 0 | 3.75 |
Reject
|
3;4;5;3
| null |
null |
Stanford University
|
2017
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Theory;Unsupervised Learning;Games
| null | 0 | null | null |
iclr
| -0.866025 | 0 | null |
main
| 6.666667 |
6;7;7
| null | null |
Optimal Binary Autoencoding with Pairwise Correlations
| null | null | 0 | 3 |
Poster
|
4;3;2
| null |
null |
Department of Computer Science, New York University, Facebook Artificial Intelligence Research
|
2017
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Deep learning;Unsupervised Learning;Semi-Supervised Learning
| null | 0 | null | null |
iclr
| -0.5 | 0 | null |
main
| 7.333333 |
7;7;8
| null | null |
Energy-based Generative Adversarial Networks
| null | null | 0 | 3.666667 |
Poster
|
5;3;3
| null |
null |
University of Kaiserslautern, Germany; German Research Center for Artificial Intelligence (DFKI), Germany; University of Kaiserslautern, Germany; German Research Center for Artificial Intelligence (DFKI), Germany
|
2017
| 0 | null | null | 0 | null | null | null | null | null | null | null | null | null | 0 | null | null |
iclr
| -0.5 | 0 | null |
main
| 5.333333 |
5;5;6
| null | null |
Classless Association using Neural Networks
| null | null | 0 | 3.333333 |
Reject
|
3;4;3
| null |
null |
Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
|
2017
| 0 | null | null | 0 | null | null | null | null | null | null | null | null | null | 0 | null | null |
iclr
| 1 | 0 | null |
main
| 6.666667 |
6;6;8
| null | null |
Towards Deep Interpretability (MUS-ROVER II): Learning Hierarchical Representations of Tonal Music
| null | null | 0 | 3.333333 |
Poster
|
3;3;4
| null |
null |
OpenAI; The University of Texas at Austin
|
2017
| 0 | null | null | 0 | null | null | null | null | null | null | null | null | null | 0 | null | null |
iclr
| -0.5 | 0 | null |
main
| 4.666667 |
4;5;5
| null | null |
Extensions and Limitations of the Neural GPU
| null | null | 0 | 3.666667 |
Reject
|
4;4;3
| null |
null |
Google Inc.
|
2017
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Deep learning
| null | 0 | null | null |
iclr
| -1 | 0 | null |
main
| 7.666667 |
7;8;8
| null | null |
Deep Learning with Dynamic Computation Graphs
|
http://github.com/tensorflow/fold
| null | 0 | 3.666667 |
Poster
|
5;3;3
| null |
null |
University of Innsbruck; Google Research
|
2017
| 0 | null | null | 0 | null | null | null | null | null |
Cezary Kaliszyk, François Chollet, Christian Szegedy
| null | null | null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 7 |
6;7;8
| null | null |
HolStep: A Machine Learning Dataset for Higher-order Logic Theorem Proving
| null | null | 0 | 3 |
Poster
|
3;3;3
| null |
null |
Department of Computational Perception, Johannes Kepler University Linz, Linz, 4040, Austria; The Austrian Research Institute for Artificial Intelligence, Vienna, 1010, Austria
|
2017
| 0 | null | null | 0 | null | null | null | null | null |
Matthias Dorfer, Jan Schlüter and Gerhard Widmer
| null |
Multi-modal learning
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 3.333333 |
3;3;4
| null | null |
Differentiable Canonical Correlation Analysis
| null | null | 0 | 4 |
Reject
|
4;4;4
| null |
null |
Google Brain; Department of Computer Science, Princeton University
|
2017
| 0 | null | null | 0 | null | null | null | null | null | null | null | null | null | 0 | null | null |
iclr
| -0.654654 | 0 | null |
main
| 6.333333 |
5;6;8
| null | null |
Identity Matters in Deep Learning
| null | null | 0 | 4 |
Poster
|
4;5;3
| null |
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null | null | null | 2.5 | null | null |
iclr
| 0 | 0 | null |
main
| 3.5 |
3;3;3;5
|
2;3;1;2
| null |
Towards Uncertainties in Deep Learning that Are Accurate and Calibrated
| null | null | 2 | 3 |
Reject
|
3;4;2;3
|
3;2;2;3
|
null | null |
2022
| 2.6 | null | null | 0 | null | null | null |
3;2;3;2;3
| null | null | null |
deep generative models;variational autoencoders
| null | 2.8 | null | null |
iclr
| -0.666667 | 0.583333 | null |
main
| 4.4 |
3;3;5;5;6
|
2;2;2;4;3
| null |
Mind Your Bits and Errors: Prioritizing the Bits that Matter in Variational Autoencoders
| null | null | 2.6 | 3.8 |
Reject
|
4;4;4;4;3
|
2;2;4;2;4
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
graph neural networks
| null | 1.5 | null | null |
iclr
| -1 | 0.57735 | null |
main
| 2.5 |
1;3;3;3
|
2;3;3;2
| null |
How Frequency Effect Graph Neural Networks
| null | null | 2.5 | 4.25 |
Withdraw
|
5;4;4;4
|
2;2;2;0
|
null | null |
2022
| 2.8 | null | null | 0 | null | null | null |
3;1;3;3;4
| null | null | null |
word embeddings;sense embeddings;word sense induction
| null | 2.4 | null | null |
iclr
| -0.48795 | 0.866025 | null |
main
| 5 |
3;5;5;6;6
|
2;3;3;3;4
| null |
Word Sense Induction with Knowledge Distillation from BERT
| null | null | 3 | 3.8 |
Reject
|
4;5;4;3;3
|
3;2;2;3;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
1;3;2;2
| null | null | null |
magnitude;magnitude vector;edge detection;adversarial robustness;metric space;algebraic topology
| null | 2.25 | null | null |
iclr
| 0 | 0 | null |
main
| 3 |
3;3;3;3
|
3;3;3;2
| null |
The magnitude vector of images
| null | null | 2.75 | 3.5 |
Reject
|
4;3;3;4
|
2;3;2;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
1;2;2;3
| null | null | null |
Dependent data sampling;SGD;sample complexity
| null | 2.25 | null | null |
iclr
| -0.648886 | 0.688247 | null |
main
| 4.75 |
3;5;5;6
|
3;3;4;4
| null |
How to Improve Sample Complexity of SGD over Highly Dependent Data?
| null | null | 3.5 | 4 |
Reject
|
5;3;4;4
|
2;2;2;3
|
null | null |
2022
| 2.2 | null | null | 0 | null | null | null |
2;2;2;2;3
| null | null | null |
Optimal Transport;Adversarial Machine Learning;Adversarial Training
| null | 2.2 | null | null |
iclr
| 0.25 | -0.25 | null |
main
| 5.2 |
5;5;5;5;6
|
3;3;4;3;3
| null |
Improving Robustness with Optimal Transport based Adversarial Generalization
| null | null | 3.2 | 3.6 |
Withdraw
|
4;4;4;2;4
|
2;2;0;4;3
|
null |
Under double-blind review
|
2022
| 3 | null | null | 0 | null | null | null |
2;3;3;4
| null | null | null | null | null | 3.25 | null | null |
iclr
| -0.160128 | 0.585369 | null |
main
| 5.5 |
3;5;6;8
|
2;2;4;3
| null |
Model Validation Using Mutated Training Labels: An Exploratory Study
| null | null | 2.75 | 3.75 |
Reject
|
4;4;3;4
|
3;2;4;4
|
null |
Google Research, Brain Team
|
2022
| 3.5 |
https://iclr.cc/virtual/2022/poster/6746; None
| null | 0 | null | null | null |
3;4;3;4
| null |
Nicolas Papernot, Thomas Steinke
|
https://iclr.cc/virtual/2022/poster/6746
|
differential privacy;hyperparameter tuning
| null | 3.25 | null |
https://openreview.net/forum?id=-70L8lpp9DF
|
iclr
| 0.426401 | 0 | null |
main
| 8 |
6;8;8;10
|
4;3;4;4
|
https://iclr.cc/virtual/2022/poster/6746
|
Hyperparameter Tuning with Renyi Differential Privacy
| null | null | 3.75 | 3.75 |
Oral
|
4;3;3;5
|
3;3;3;4
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
3;2;2;2
| null | null | null | null | null | 2 | null | null |
iclr
| -0.904534 | -1 | null |
main
| 4 |
3;3;5;5
|
4;4;3;3
| null |
Deep Ensemble Policy Learning
| null | null | 3.5 | 4.25 |
Withdraw
|
5;5;3;4
|
2;2;2;2
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;3;2
| null | null | null |
Implicit Policy;State-action Visitation;Distribution Matching;Generative Adversarial Networks
| null | 3 | null | null |
iclr
| 0 | 1 | null |
main
| 5 |
3;6;6
|
2;3;3
| null |
State-Action Joint Regularized Implicit Policy for Offline Reinforcement Learning
| null | null | 2.666667 | 4 |
Reject
|
4;4;4
|
3;3;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
1;2;3;3
| null | null | null | null | null | 2.25 | null | null |
iclr
| -1 | 0.816497 | null |
main
| 4.5 |
3;5;5;5
|
2;3;4;3
| null |
Implicit vs Unfolded Graph Neural Networks
| null | null | 3 | 3.25 |
Withdraw
|
4;3;3;3
|
2;2;3;2
|
null |
IBM Research - Zurich, SynSense, Zürich, Switzerland, ETH Zürich, Switzerland; ETH Zürich, Switzerland; SynSense, Zürich, Switzerland
|
2022
| 2.666667 |
https://iclr.cc/virtual/2022/poster/7062; None
| null | 0 | null | null | null |
3;2;3
| null |
Julian Büchel, Fynn Faber, Dylan R Muir
|
https://iclr.cc/virtual/2022/poster/7062
|
parameter attack;adversarial attack;neural network;deep learning;optimisation;neuromorphic processor
| null | 3 | null |
https://openreview.net/forum?id=-8sBpe7rDiV
|
iclr
| 0 | 0 | null |
main
| 6.666667 |
6;6;8
|
4;4;4
|
https://iclr.cc/virtual/2022/poster/7062
|
NETWORK INSENSITIVITY TO PARAMETER NOISE VIA PARAMETER ATTACK DURING TRAINING
| null | null | 4 | 3 |
Poster
|
2;4;3
|
3;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
cognitive science;variational Bayes;category representation;sparse coding;representation learning;interpretable representations
| null | 1.75 | null | null |
iclr
| -0.555556 | 0 | null |
main
| 4.25 |
3;3;5;6
|
2;4;3;3
| null |
VICE: Variational Inference for Concept Embeddings
| null | null | 3 | 3.25 |
Reject
|
4;3;3;3
|
2;1;2;2
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;3;3;3
| null | null | null |
reinforcement learning;representation learning;mutual information
| null | 2.5 | null | null |
iclr
| -1 | 0.333333 | null |
main
| 5.25 |
5;5;5;6
|
3;3;2;3
| null |
Learning Controllable Elements Oriented Representations for Reinforcement Learning
| null | null | 2.75 | 3.75 |
Reject
|
4;4;4;3
|
3;2;2;3
|
null |
Department of Information Engineering and Computer Science (DISI), University of Trento, Trento, TN 38123, Italy
|
2022
| 2.666667 |
https://iclr.cc/virtual/2022/poster/6545; None
| null | 0 | null | null | null |
3;3;2
| null |
Yue Song, Nicu Sebe, Wei Wang
|
https://iclr.cc/virtual/2022/poster/6545
|
Differentiabl Matrix Square Root;Differentiable Matrix Decomposition;Vision Transformers
| null | 3 | null |
https://openreview.net/forum?id=-AOEi-5VTU8
|
iclr
| 0 | 0 | null |
main
| 8 |
8;8;8
|
4;3;4
|
https://iclr.cc/virtual/2022/poster/6545
|
Fast Differentiable Matrix Square Root
|
https://github.com/KingJamesSong/FastDifferentiableMatSqrt
| null | 3.666667 | 4.333333 |
Poster
|
4;5;4
|
3;3;3
|
null | null |
2022
| 1.666667 | null | null | 0 | null | null | null |
1;2;2
| null | null | null | null | null | 1.666667 | null | null |
iclr
| -0.5 | 1 | null |
main
| 2.333333 |
1;3;3
|
2;3;3
| null |
Dissecting Local Properties of Adversarial Examples
| null | null | 2.666667 | 3.666667 |
Reject
|
4;4;3
|
1;2;2
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
face restoration;generative model
| null | 2.25 | null | null |
iclr
| -0.408248 | -0.408248 | null |
main
| 5 |
3;5;6;6
|
3;2;2;3
| null |
Rethinking Deep Face Restoration
| null | null | 2.5 | 4.5 |
Withdraw
|
5;4;5;4
|
2;2;2;3
|
null |
Carnegie Mellon University, Pittsburgh, USA; Inria (Parietal), Gif-sur-Yvette, France; AIM, CEA, CNRS, Gif-sur-Yvette, France; University of Graz, Graz, Austria; CEA (Neurospin & Cosmostat), Inria (Parietal), Gif-sur-Yvette, France; CEA (Neurospin), Inria (Parietal), Gif-sur-Yvette, France
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6363; None
| null | 0 | null | null | null |
3;3;3
| null |
Zaccharie Ramzi, Florian Mannel, Shaojie Bai, Jean-Luc Starck, Philippe Ciuciu, Thomas Moreau
|
https://iclr.cc/virtual/2022/poster/6363
|
implicit models;bi-level optimization;quasi-newton methods
| null | 2.666667 | null |
https://openreview.net/forum?id=-ApAkox5mp
|
iclr
| 0 | 0 | null |
main
| 8 |
8;8;8
|
4;3;4
|
https://iclr.cc/virtual/2022/poster/6363
|
SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models
| null | null | 3.666667 | 3 |
Spotlight
|
3;3;3
|
2;3;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
Class-Incremental Learning;Semantic Segmentation;Evidential Deep Learrning;Deep Neural Networks;Class-Incremental Semantic Segmentation;Continual-Learning
| null | 1.25 | null | null |
iclr
| 0 | 0.707107 | null |
main
| 4 |
3;3;5;5
|
2;3;4;3
| null |
Modeling Unknown Semantic Labels as Uncertainty in the Prediction: Evidential Deep Learning for Class-Incremental Semantic Segmentation
| null | null | 3 | 4 |
Withdraw
|
4;4;4;4
|
1;2;0;2
|
null | null |
2022
| 2.8 | null | null | 0 | null | null | null |
2;2;3;3;4
| null | null | null |
out-of-distribution detection;robustness;OOD
| null | 1.8 | null | null |
iclr
| 0.095871 | 0.962533 | null |
main
| 6.6 |
3;6;6;8;10
|
2;3;3;4;4
| null |
Revisiting Out-of-Distribution Detection: A Simple Baseline is Surprisingly Effective
| null | null | 3.2 | 3 |
Reject
|
2;4;4;2;3
|
2;2;2;3;0
|
null | null |
2022
| 1.6 | null | null | 0 | null | null | null |
1;2;1;2;2
| null | null | null |
Reinforcement Learning;Interpretability;Explainable Artificial Intelligence;Neural Networks
| null | 1.2 | null | null |
iclr
| -0.408248 | 0.408248 | null |
main
| 1.8 |
1;1;1;3;3
|
2;2;1;2;2
| null |
Self Reward Design with Fine-grained Interpretability
| null | null | 1.8 | 3.4 |
Reject
|
3;4;4;2;4
|
2;1;1;2;0
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
1;2;3
| null | null | null | null | null | 2 | null | null |
iclr
| 0 | 0.866025 | null |
main
| 3 |
1;3;5
|
2;2;3
| null |
A Reinforcement Learning Environment for Mathematical Reasoning via Program Synthesis
| null | null | 2.333333 | 4 |
Withdraw
|
4;4;4
|
1;2;3
|
null |
LTS4, EPFL, Lausanne, Switzerland
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6635; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Clément Vignac, Pascal Frossard
|
https://iclr.cc/virtual/2022/poster/6635
|
set generation;graph generation;permutation equivariance;generative models;Top-N
| null | 2.25 | null |
https://openreview.net/forum?id=-Gk_IPJWvk
|
iclr
| 0.132453 | 0.973329 | null |
main
| 6.25 |
5;6;6;8
|
2;3;3;4
|
https://iclr.cc/virtual/2022/poster/6635
|
Top-N: Equivariant Set and Graph Generation without Exchangeability
| null | null | 3 | 3.75 |
Poster
|
4;3;4;4
|
2;3;2;2
|
null | null |
2022
| 2.4 | null | null | 0 | null | null | null |
2;2;2;3;3
| null | null | null | null | null | 2.2 | null | null |
iclr
| -0.575224 | 0.943242 | null |
main
| 5.2 |
3;5;6;6;6
|
2;3;3;3;3
| null |
Fundamental Limits of Transfer Learning in Binary Classifications
| null | null | 2.8 | 3 |
Reject
|
4;3;2;2;4
|
2;1;3;2;3
|
null |
Department of Electrical and Computer Engineering, Ohio State University, Columbus, OH 43210, USA
|
2022
| 3.5 |
https://iclr.cc/virtual/2022/poster/6938; None
| null | 0 | null | null | null |
3;3;4;4
| null |
Ziwei Guan, Tengyu Xu, Yingbin Liang
|
https://iclr.cc/virtual/2022/poster/6938
|
emphatic temporal difference;finite-time analysis;off-policy evaluation;reinforcement learning
| null | 2.5 | null |
https://openreview.net/forum?id=-HSOjDPfhBJ
|
iclr
| 0 | 0 | null |
main
| 8 |
8;8;8;8
|
4;3;4;4
|
https://iclr.cc/virtual/2022/poster/6938
|
PER-ETD: A Polynomially Efficient Emphatic Temporal Difference Learning Method
| null | null | 3.75 | 3 |
Poster
|
3;3;3;3
|
3;3;2;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2
| null | null | null |
Clustering
| null | 2 | null | null |
iclr
| 0.755929 | 0 | null |
main
| 4.666667 |
3;5;6
|
3;3;3
| null |
Language-Guided Image Clustering
| null | null | 3 | 3.333333 |
Withdraw
|
3;3;4
|
2;2;2
|
null | null |
2022
| 2.4 | null | null | 0 | null | null | null |
3;2;3;1;3
| null | null | null |
multi-task learning;dynamic networks;adaptive inference;neural network
| null | 2 | null | null |
iclr
| 0 | 0 | null |
main
| 3 |
3;3;3;3;3
|
2;3;2;3;2
| null |
DYNASHARE: DYNAMIC NEURAL NETWORKS FOR MULTI-TASK LEARNING
| null | null | 2.4 | 4.2 |
Withdraw
|
4;4;4;4;5
|
3;3;2;1;1
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
2;3;2
| null | null | null | null | null | 2 | null | null |
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6
|
4;3;4
| null |
Multi-agent Performative Prediction: From Global Stability and Optimality to Chaos
| null | null | 3.666667 | 3.333333 |
Reject
|
4;3;3
|
2;2;2
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null | null | null | 2.75 | null | null |
iclr
| 0.333333 | 1 | null |
main
| 4.5 |
3;5;5;5
|
2;3;3;3
| null |
Zero-Round Active Learning
| null | null | 2.75 | 4.25 |
Withdraw
|
4;4;4;5
|
2;3;3;3
|
null | null |
2022
| 3.2 | null | null | 0 | null | null | null |
3;3;3;3;4
| null | null | null |
graph neural networks;expressive power;complexity
| null | 1.6 | null | null |
iclr
| 0.612372 | 0.408248 | null |
main
| 5.6 |
5;5;6;6;6
|
3;3;3;3;4
| null |
Counting Substructures with Higher-Order Graph Neural Networks: Possibility and Impossibility Results
| null | null | 3.2 | 3.6 |
Reject
|
3;3;4;3;5
|
2;0;2;2;2
|
null |
University of California, Los Angeles; Northwestern University; Dartmouth College; University of Texas, Austin
|
2022
| 2.6 |
https://iclr.cc/virtual/2022/poster/6175; None
| null | 0 | null | null | null |
2;2;3;3;3
| null |
Ruibo Liu, CHONGYANG GAO, Chenyan Jia, Guangxuan Xu, Soroush Vosoughi
|
https://iclr.cc/virtual/2022/poster/6175
|
style transfer;non-parallel corpus;imitation learning;language models;political stance transfer
| null | 2.8 | null |
https://openreview.net/forum?id=-TSe5o7STVR
|
iclr
| 0 | 0.49099 | null |
main
| 6.2 |
3;6;6;8;8
|
3;3;3;4;3
|
https://iclr.cc/virtual/2022/poster/6175
|
Non-Parallel Text Style Transfer with Self-Parallel Supervision
| null | null | 3.2 | 4 |
Poster
|
4;3;5;4;4
|
3;3;2;3;3
|
null | null |
2022
| 1.666667 | null | null | 0 | null | null | null |
1;2;2
| null | null | null | null | null | 2.333333 | null | null |
iclr
| -1 | -0.5 | null |
main
| 4.333333 |
3;5;5
|
4;3;4
| null |
Safe Deep RL in 3D Environments using Human Feedback
| null | null | 3.666667 | 3.333333 |
Reject
|
4;3;3
|
2;2;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;1;3
| null | null | null |
Backdoor Attacks;Multi-Agent Reinforcement Learning
| null | 1.5 | null | null |
iclr
| -0.816497 | 0.333333 | null |
main
| 3.5 |
3;3;3;5
|
2;3;3;3
| null |
MARNET: Backdoor Attacks against Value-Decomposition Multi-Agent Reinforcement Learning
| null | null | 2.75 | 3 |
Withdraw
|
3;4;3;2
|
2;0;1;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;1;3;3
| null | null | null |
Exploration;Uncertainty;Reinforcement Learning
| null | 2.75 | null | null |
iclr
| 0 | 0.57735 | null |
main
| 4.5 |
3;3;6;6
|
2;2;2;3
| null |
OVD-Explorer: A General Information-theoretic Exploration Approach for Reinforcement Learning
| null | null | 2.25 | 3 |
Reject
|
3;3;3;3
|
3;2;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null | null | null | 1.75 | null | null |
iclr
| 0 | 0 | null |
main
| 3 |
3;3;3;3
|
3;2;1;2
| null |
A Compositional Approach to Occlusion in Panoptic Segmentation
| null | null | 2 | 4 |
Withdraw
|
4;4;3;5
|
2;1;1;3
|
null | null |
2022
| 1.75 | null | null | 0 | null | null | null |
1;2;2;2
| null | null | null |
AutoML;NAS;Neural Architecture Search;Ranking
| null | 2 | null | null |
iclr
| -0.333333 | 0.333333 | null |
main
| 3.5 |
3;3;3;5
|
3;2;3;3
| null |
Ranking Convolutional Architectures by their Feature Extraction Capabilities
| null | null | 2.75 | 4.25 |
Withdraw
|
4;4;5;4
|
2;2;2;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
machine learning;deep learning;orthogonalisation;optmisation;optimization
| null | 2 | null | null |
iclr
| 0 | 0 | null |
main
| 3 |
3;3;3;3
|
2;2;2;2
| null |
Orthogonalising gradients to speedup neural network optimisation
| null | null | 2 | 4.5 |
Reject
|
4;5;4;5
|
2;2;2;2
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;2;3;4
| null | null | null | null | null | 2.25 | null | null |
iclr
| -0.710669 | 0.544331 | null |
main
| 5 |
3;3;6;8
|
3;2;3;3
| null |
Equalized Robustness: Towards Sustainable Fairness Under Distributional Shifts
| null | null | 2.75 | 3.25 |
Reject
|
4;4;2;3
|
1;2;3;3
|
null |
1University of Cambridge, 2MPI for Intelligent Systems; 1University of Cambridge, 5The Alan Turing Institute; 2MPI for Intelligent Systems; 3Stanford University, 4Google Research
|
2022
| 3.333333 |
https://iclr.cc/virtual/2022/poster/6685; None
| null | 0 | null | null | null |
3;3;4
| null |
Chaochao Lu, Yuhuai Wu, José Miguel Hernández Lobato, Bernhard Schoelkopf
|
https://iclr.cc/virtual/2022/poster/6685
| null | null | 3.333333 | null |
https://openreview.net/forum?id=-e4EXDWXnSn
|
iclr
| 0 | 1 | null |
main
| 6.666667 |
6;6;8
|
3;3;4
|
https://iclr.cc/virtual/2022/poster/6685
|
Invariant Causal Representation Learning for Out-of-Distribution Generalization
| null | null | 3.333333 | 3 |
Poster
|
3;3;3
|
3;3;4
|
null | null |
2022
| 1.8 | null | null | 0 | null | null | null |
1;2;2;2;2
| null | null | null |
sparsity;natural language processing;pre-training;computational efficiency
| null | 2.4 | null | null |
iclr
| -0.592927 | -0.395285 | null |
main
| 4 |
3;3;3;5;6
|
3;3;3;2;3
| null |
Towards Structured Dynamic Sparse Pre-Training of BERT
| null | null | 2.8 | 3.4 |
Reject
|
4;4;3;4;2
|
2;2;2;3;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
1;3;2;3
| null | null | null |
Working Memory;RNN;Dynamical Systems;Slow Manifold;Gating
| null | 2.25 | null | null |
iclr
| -0.70014 | -0.140028 | null |
main
| 5.75 |
3;6;6;8
|
4;3;3;4
| null |
Gating Mechanisms Underlying Sequence-to-Sequence Working Memory
| null | null | 3.5 | 3.5 |
Reject
|
4;3;4;3
|
1;1;3;4
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;2;3
| null | null | null |
density-based clustering;diffusion process;density function;face clustering
| null | 2.25 | null | null |
iclr
| 0.816497 | 0.333333 | null |
main
| 4.5 |
3;5;5;5
|
2;3;2;2
| null |
Density-based Clustering with Kernel Diffusion
| null | null | 2.25 | 4 |
Reject
|
3;5;4;4
|
3;2;2;2
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;2;4
| null | null | null |
Adversarial training;Robust overfitting;Double descent;Label noise
| null | 2.25 | null | null |
iclr
| 0 | -0.57735 | null |
main
| 5.75 |
5;6;6;6
|
4;4;3;3
| null |
Double Descent in Adversarial Training: An Implicit Label Noise Perspective
| null | null | 3.5 | 4 |
Reject
|
4;4;3;5
|
2;3;0;4
|
null |
University of Zurich
|
2022
| 2.8 |
https://iclr.cc/virtual/2022/poster/5935; None
| null | 0 | null | null | null |
2;3;2;4;3
| null |
Ada Wan
|
https://iclr.cc/virtual/2022/poster/5935
|
fairness;evaluation;multilingual NLP / multilinguality;representation learning for language data;statistical comparisons;Double Descent;conditional language modeling;data-centric approach;diversity in AI;morphology;Transformer;meta evaluation;visualization or interpretation of learned representations;character encoding;internationalization and localization;robustness;statistical science for NLP;science in the era of AI/DL (AIxScience);transdisciplinarity
| null | 3 | null |
https://openreview.net/forum?id=-llS6TiOew
|
iclr
| -0.218218 | 0 | null |
main
| 7.2 |
6;6;8;8;8
|
3;3;3;3;3
|
https://iclr.cc/virtual/2022/poster/5935
|
Fairness in Representation for Multilingual NLP: Insights from Controlled Experiments on Conditional Language Modeling
| null | null | 3 | 3.8 |
Spotlight
|
3;5;4;3;4
|
2;3;3;4;3
|
null |
School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University; Anhui University
|
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6435; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Xiaoyang Huang, Jiancheng Yang, Yanjun Wang, Ziyu Chen, Linguo Li, Teng Li, Bingbing Ni, Wenjun Zhang
|
https://iclr.cc/virtual/2022/poster/6435
|
shape embedding;3D deep learning;shape classification and segmentation
| null | 3 | null |
https://openreview.net/forum?id=-ngwPqanCEZ
|
iclr
| 0 | 1 | null |
main
| 5.5 |
5;5;6;6
|
3;3;4;4
|
https://iclr.cc/virtual/2022/poster/6435
|
Representation-Agnostic Shape Fields
|
https://github.com/seanywang0408/RASF
| null | 3.5 | 4 |
Poster
|
4;4;4;4
|
2;3;3;4
|
null | null |
2022
| 2.8 | null | null | 0 | null | null | null |
2;2;3;3;4
| null | null | null |
deep learning;anomaly detection;unsupervised learning;sequential data
| null | 2 | null | null |
iclr
| -0.375 | 0.875 | null |
main
| 3.8 |
1;3;5;5;5
|
2;3;3;3;3
| null |
S$^3$ADNet: Sequential Anomaly Detection with Pessimistic Contrastive Learning
| null | null | 2.8 | 3.8 |
Reject
|
4;4;4;3;4
|
1;2;2;3;2
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;2;4
| null | null | null | null | null | 1.666667 | null | null |
iclr
| 0.5 | -0.5 | null |
main
| 5.333333 |
5;5;6
|
3;4;3
| null |
Reynolds Equivariant and Invariant Networks
| null | null | 3.333333 | 2.666667 |
Withdraw
|
3;2;3
|
1;2;2
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;3;3;3
| null | null | null |
Machine Learning;Information Theory;Multi-Armed Bandits
| null | 2.5 | null | null |
iclr
| -0.816497 | -0.333333 | null |
main
| 5.75 |
5;6;6;6
|
4;4;4;3
| null |
Contextual Multi-Armed Bandit with Communication Constraints
| null | null | 3.75 | 3 |
Reject
|
4;3;3;2
|
2;3;2;3
|
null | null |
2022
| 2.4 | null | null | 0 | null | null | null |
2;2;2;3;3
| null | null | null |
MLP;transformers;speech signal processing
| null | 2 | null | null |
iclr
| 0.0625 | 0.875 | null |
main
| 5.2 |
3;5;5;5;8
|
3;3;3;3;4
| null |
Speech-MLP: a simple MLP architecture for speech processing
| null | null | 3.2 | 3.8 |
Reject
|
4;4;3;4;4
|
0;2;2;3;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
Meta-learning;self-attention;feature-selection
| null | 3 | null | null |
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6;6
|
3;3;3;3
| null |
Attentional meta-learners for few-shot polythetic classification
| null | null | 3 | 3.75 |
Reject
|
4;4;4;3
|
3;3;2;4
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;3;2
| null | null | null |
Multi-Agent Reinforcement Learning;Inventory Management;Shared Resource;Decentralized Training Paradigm;Model-based RL
| null | 2.25 | null | null |
iclr
| -0.57735 | 0 | null |
main
| 5.5 |
5;5;6;6
|
3;3;3;3
| null |
Multi-Agent Reinforcement Learning with Shared Resource in Inventory Management
| null | null | 3 | 3.75 |
Reject
|
4;4;4;3
|
2;2;3;2
|
null |
Department of Computer Science, University of Oxford; GlaxoSmithKline, Artificial Intelligence & Machine Learning; MIT
|
2022
| 2 |
https://iclr.cc/virtual/2022/poster/6889; None
| null | 0 | null | null | null |
1;3;2
| null |
Arash Mehrjou, Ashkan Soleymani, Andrew Jesson, Pascal Notin, Yarin Gal, Stefan Bauer, Patrick Schwab
|
https://iclr.cc/virtual/2022/poster/6889
|
batch active learning;drug discovery;benchmark
| null | 3 | null |
https://openreview.net/forum?id=-w2oomO6qgc
|
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6
|
3;3;3
|
https://iclr.cc/virtual/2022/poster/6889
|
GeneDisco: A Benchmark for Experimental Design in Drug Discovery
| null | null | 3 | 3.666667 |
Poster
|
4;4;3
|
3;4;2
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;4;2
| null | null | null |
Inductive Relation Prediction;Topological Data Analysis;Cycle Basis;Homology
| null | 2.5 | null | null |
iclr
| -0.522233 | 0.522233 | null |
main
| 3.5 |
1;3;5;5
|
2;2;4;2
| null |
A Topological View of Rule Learning in Knowledge Graphs
| null | null | 2.5 | 3.75 |
Reject
|
4;4;3;4
|
2;3;3;2
|
null | null |
2022
| 1.75 | null | null | 0 | null | null | null |
2;2;1;2
| null | null | null |
multi-task learning;MTL;reinforcement learning;machine learning;routing networks;modular networks
| null | 1.5 | null | null |
iclr
| 0 | 0 | null |
main
| 3 |
3;3;3;3
|
3;2;4;3
| null |
LRN: Limitless Routing Networks for Effective Multi-task Learning
| null | null | 3 | 4.25 |
Reject
|
4;5;4;4
|
2;1;1;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
temporal point process;event sequence clustering;deep learning
| null | 1.5 | null | null |
iclr
| 0 | 0.57735 | null |
main
| 4 |
3;3;5;5
|
3;3;3;4
| null |
Learning mixture of neural temporal point processes for event sequence clustering
| null | null | 3.25 | 4 |
Withdraw
|
4;4;4;4
|
2;0;2;2
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
data augmentation;self-supervision;video representation
| null | 1.75 | null | null |
iclr
| -0.174078 | 0.333333 | null |
main
| 3.5 |
3;3;3;5
|
3;3;2;3
| null |
Vi-MIX FOR SELF-SUPERVISED VIDEO REPRESENTATION
| null | null | 2.75 | 4.25 |
Withdraw
|
5;5;3;4
|
2;1;2;2
|
null | null |
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/6204; None
| null | 0 | null | null | null |
3;3;3;2
| null |
Hae Beom Lee, Hayeon Lee, JaeWoong Shin, Eunho Yang, Timothy Hospedales, Sung Ju Hwang
|
https://iclr.cc/virtual/2022/poster/6204
|
Hyperparameter Optimization;Meta-learning
| null | 3 | null |
https://openreview.net/forum?id=01AMRlen9wJ
|
iclr
| -0.707107 | 0.57735 | null |
main
| 7 |
6;6;8;8
|
3;3;3;4
|
https://iclr.cc/virtual/2022/poster/6204
|
Online Hyperparameter Meta-Learning with Hypergradient Distillation
| null | null | 3.25 | 3 |
Spotlight
|
3;4;2;3
|
3;3;3;3
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
3;2;2;3
| null | null | null |
GAN;Latent Space;Latent semantics;Regression;Few-Shot
| null | 2.75 | null | null |
iclr
| 0 | 0.57735 | null |
main
| 5.75 |
5;5;5;8
|
3;3;4;4
| null |
LARGE: Latent-Based Regression through GAN Semantics
| null | null | 3.5 | 4 |
Withdraw
|
4;4;4;4
|
3;3;2;3
|
null | null |
2022
| 2.75 |
https://iclr.cc/virtual/2022/poster/7063; None
| null | 0 | null | null | null |
2;3;3;3
| null |
Tian Xie, Xiang Fu, Octavian Ganea, Regina Barzilay, Tommi Jaakkola
|
https://iclr.cc/virtual/2022/poster/7063
|
materials;graph neural networks;periodic;diffusion models;score matching;molecule;3D;generative
| null | 3.25 | null |
https://openreview.net/forum?id=03RLpj-tc_
|
iclr
| 0.160128 | 0.83205 | null |
main
| 5.5 |
3;5;6;8
|
3;3;4;4
|
https://iclr.cc/virtual/2022/poster/7063
|
Crystal Diffusion Variational Autoencoder for Periodic Material Generation
| null | null | 3.5 | 4.25 |
Poster
|
4;4;5;4
|
3;3;3;4
|
null | null |
2022
| 2.8 |
https://iclr.cc/virtual/2022/poster/6851; None
| null | 0 | null | null | null |
3;2;3;3;3
| null |
FNU Hairi, Jia Liu, Songtao Lu
|
https://iclr.cc/virtual/2022/poster/6851
| null | null | 2 | null |
https://openreview.net/forum?id=04pGUg0-pdZ
|
iclr
| 0.166667 | 0.666667 | null |
main
| 6.8 |
6;6;6;8;8
|
4;3;3;4;4
|
https://iclr.cc/virtual/2022/poster/6851
|
Finite-Time Convergence and Sample Complexity of Multi-Agent Actor-Critic Reinforcement Learning with Average Reward
| null | null | 3.6 | 3.4 |
Spotlight
|
3;3;4;3;4
|
2;1;2;2;3
|
null | null |
2022
| 2.2 | null | null | 0 | null | null | null |
1;2;2;2;4
| null | null | null |
emergent language;reinforcement learning;neural networks
| null | 2.2 | null | null |
iclr
| 0.102062 | 0.6875 | null |
main
| 3.2 |
1;3;3;3;6
|
2;3;3;3;3
| null |
Shaped Rewards Bias Emergent Language
| null | null | 2.8 | 3.6 |
Reject
|
4;4;3;3;4
|
1;2;2;2;4
|
null |
Singapore Institute of Manufacturing Technology, A*STAR, Singapore; Institute of Marine Science and Technology, Shandong University, Qingdao, China; School of Computer Science and Engineering, Nanyang Technological University, Singapore
|
2022
| 2 |
https://iclr.cc/virtual/2022/poster/7065; None
| null | 0 | null | null | null |
2;2;2
| null |
Yaoxin Wu, Wen Song, Zhiguang Cao, Jie Zhang
|
https://iclr.cc/virtual/2022/poster/7065
|
Conditional Variational Autoencoder;Stochastic Integer Programming;Scenario Reduction
| null | 2.666667 | null |
https://openreview.net/forum?id=06Wy2BtxXrz
|
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6
|
3;3;4
|
https://iclr.cc/virtual/2022/poster/7065
|
Learning Scenario Representation for Solving Two-stage Stochastic Integer Programs
| null | null | 3.333333 | 2.666667 |
Poster
|
3;2;3
|
2;3;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;3;2
| null | null | null |
differential privacy;differentially private SGD;privacy-preserving training
| null | 2.75 | null | null |
iclr
| -0.57735 | 1 | null |
main
| 4.5 |
3;5;5;5
|
2;3;3;3
| null |
Differentially Private SGD with Sparse Gradients
| null | null | 2.75 | 3.5 |
Reject
|
4;3;3;4
|
2;2;4;3
|
null |
Department of Electrical&Computer Engineering, University of Minnesota; Center for Magnetic Resonance Research, University of Minnesota
|
2022
| 2.333333 |
https://iclr.cc/virtual/2022/poster/6862; None
| null | 0 | null | null | null |
2;2;3
| null |
Burhaneddin Yaman, Seyed Amir Hossein Hosseini, Mehmet Akcakaya
|
https://iclr.cc/virtual/2022/poster/6862
|
Zero-shot learning;Self-supervised learning;MRI Reconstruction;Transfer learning;Physics-guided deep learning
| null | 2.666667 | null |
https://openreview.net/forum?id=085y6YPaYjP
|
iclr
| -0.5 | -0.5 | null |
main
| 5.333333 |
5;5;6
|
4;3;3
|
https://iclr.cc/virtual/2022/poster/6862
|
Zero-Shot Self-Supervised Learning for MRI Reconstruction
| null | null | 3.333333 | 4.333333 |
Poster
|
5;4;4
|
2;3;3
|
null |
University of Freiburg; University of Freiburg, Bosch Center for AI; Abacus.AI
|
2022
| 2.25 |
https://iclr.cc/virtual/2022/poster/7126; None
| null | 0 | null | null | null |
2;1;3;3
| null |
Yash Mehta, Colin White, Arber Zela, Arjun Krishnakumar, Guri Zabergja, Shakiba Moradian, Mahmoud Safari, Kaicheng Yu, Frank Hutter
|
https://iclr.cc/virtual/2022/poster/7126
|
neural architecture search;AutoML
| null | 3.25 | null |
https://openreview.net/forum?id=0DLwqQLmqV
|
iclr
| 0 | -0.333333 | null |
main
| 7.5 |
6;8;8;8
|
4;3;4;4
|
https://iclr.cc/virtual/2022/poster/7126
|
NAS-Bench-Suite: NAS Evaluation is (Now) Surprisingly Easy
|
https://github.com/automl/naslib
| null | 3.75 | 4 |
Poster
|
4;5;4;3
|
3;4;3;3
|
null |
Stanford University
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/6846; None
| null | 0 | null | null | null |
2;2;3;3
| null |
Eric Mitchell, Charles Lin, Antoine Bosselut, Chelsea Finn, Christopher Manning
|
https://iclr.cc/virtual/2022/poster/6846
|
editing;transfomers;meta-learning
| null | 2.75 | null |
https://openreview.net/forum?id=0DcZxeWfOPt
|
iclr
| 0.070535 | 0.493742 |
https://sites.google.com/view/mend-editing
|
main
| 6.25 |
3;6;8;8
|
3;3;4;3
|
https://iclr.cc/virtual/2022/poster/6846
|
Fast Model Editing at Scale
| null | null | 3.25 | 3.75 |
Poster
|
4;3;4;4
|
2;2;3;4
|
null | null |
2022
| 1.25 | null | null | 0 | null | null | null |
1;1;2;1
| null | null | null |
cGAN;CFD;Image-to-Image;Fluid Simulation
| null | 1 | null | null |
iclr
| -0.57735 | -0.301511 | null |
main
| 2 |
1;1;3;3
|
2;3;3;1
| null |
A New Perspective on Fluid Simulation: An Image-to-Image Translation Task via Neural Networks
| null | null | 2.25 | 4.75 |
Reject
|
5;5;5;4
|
1;1;2;0
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;3;3;2
| null | null | null |
Multi-Agent Reinforcement Learning (MARL);Offline reinforcement learning (RL);Offline Multi-Agent Reinforcement Learning
| null | 2.5 | null | null |
iclr
| -0.57735 | 1 | null |
main
| 5.5 |
5;5;6;6
|
3;3;4;4
| null |
Plan Better Amid Conservatism: Offline Multi-Agent Reinforcement Learning with Actor Rectification
| null | null | 3.5 | 3.25 |
Reject
|
3;4;3;3
|
2;3;3;2
|
null |
Shanghai Jiaotong University; Ant Group; Ant Group, Shanghai Jiaotong University; TU Wien, Austria
|
2022
| 3 |
https://iclr.cc/virtual/2022/poster/6827; None
| null | 0 | null | null | null |
4;2;3;3
| null |
Shi Zhan Liu, Hang Yu, Cong Liao, Jianguo Li, Weiyao Lin, Alex Liu ·
|
https://iclr.cc/virtual/2022/poster/6827
|
sparse attention;pyramidal graph;Transformer;time series forecasting;long-range dependence;multiresolution
| null | 3 | null |
https://openreview.net/forum?id=0EXmFzUn5I
|
iclr
| -0.57735 | 0.57735 | null |
main
| 7 |
6;6;8;8
|
4;3;4;4
|
https://iclr.cc/virtual/2022/poster/6827
|
Pyraformer: Low-Complexity Pyramidal Attention for Long-Range Time Series Modeling and Forecasting
|
https://github.com/alipay/Pyraformer
| null | 3.75 | 3.75 |
Oral
|
4;4;3;4
|
3;3;3;3
|
null | null |
2022
| 2.666667 | null | null | 0 | null | null | null |
3;2;3
| null | null | null |
Reinforcement Learning;Algorithmic Stability;Generalisation;Overfitting;Target Network;Fitted TD;Off-Policy;Batch Reinforcement Learning
| null | 0.666667 | null | null |
iclr
| 0 | 0 | null |
main
| 3 |
3;3;3
|
3;2;3
| null |
Stability and Generalisation in Batch Reinforcement Learning
| null | null | 2.666667 | 3.333333 |
Reject
|
4;4;2
|
2;0;0
|
null | null |
2022
| 2.5 | null | null | 0 | null | null | null |
2;2;3;3
| null | null | null |
Multi-agent Reinforcement Learning
| null | 3 | null | null |
iclr
| 0.904534 | 0.57735 | null |
main
| 5.5 |
5;5;6;6
|
3;2;3;3
| null |
Role Diversity Matters: A Study of Cooperative Training Strategies for Multi-Agent RL
| null | null | 2.75 | 3.25 |
Reject
|
3;2;4;4
|
3;2;4;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2;2
| null | null | null |
continuous-time dynamic graphs;temporal graph neural networks;graph neural networks
| null | 2.5 | null | null |
iclr
| -0.816497 | 0 | null |
main
| 5.75 |
5;6;6;6
|
3;3;3;3
| null |
Online graph nets
| null | null | 3 | 4 |
Withdraw
|
5;4;4;3
|
3;3;2;2
|
null | null |
2022
| 3 | null | null | 0 | null | null | null |
3;3;4;2
| null | null | null |
Graph Convolutional Networks;Efficient Networks
| null | 3 | null | null |
iclr
| 0.816497 | 0 | null |
main
| 5 |
3;5;6;6
|
3;3;3;3
| null |
D$^2$-GCN: Data-Dependent GCNs for Boosting Both Efficiency and Scalability
| null | null | 3 | 3.5 |
Reject
|
3;3;4;4
|
3;3;4;2
|
null |
University of Oxford, Oxford, United Kingdom; VinAI Research, Hanoi, Vietnam
|
2022
| 2.5 |
https://iclr.cc/virtual/2022/poster/6322; None
| null | 0 | null | null | null |
2;2;3;3
| null |
A. Tuan Nguyen, Toan Tran, Yarin Gal, Philip Torr, Atilim Gunes Baydin
|
https://iclr.cc/virtual/2022/poster/6322
|
domain adaptation;invariant representation
| null | 2.75 | null |
https://openreview.net/forum?id=0JzqUlIVVDd
|
iclr
| -0.140028 | 0.727607 | null |
main
| 5.75 |
3;6;6;8
|
3;3;3;4
|
https://iclr.cc/virtual/2022/poster/6322
|
KL Guided Domain Adaptation
| null | null | 3.25 | 3.5 |
Poster
|
4;3;3;4
|
2;3;3;3
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;1;3
| null | null | null |
representation learning;gesture generation;vector quantization;machine translation
| null | 1.666667 | null | null |
iclr
| -0.188982 | 0.944911 | null |
main
| 4.666667 |
3;5;6
|
2;3;3
| null |
Gesture2Vec: Clustering Gestures using Representation Learning Methods for Co-speech Gesture Generation
| null | null | 2.666667 | 4.666667 |
Reject
|
5;4;5
|
0;2;3
|
null | null |
2022
| 2.4 | null | null | 0 | null | null | null |
2;2;2;3;3
| null | null | null |
kernel continual learning;generative learning;catastrophic forgetting
| null | 2 | null | null |
iclr
| 0 | 0.645497 | null |
main
| 4.2 |
3;3;3;6;6
|
3;3;2;4;3
| null |
Generative Kernel Continual Learning
| null | null | 3 | 4 |
Withdraw
|
4;4;4;4;4
|
1;2;2;3;2
|
null | null |
2022
| 2 | null | null | 0 | null | null | null |
2;2;2
| null | null | null |
few-shot learning;noisy labels;variational inference;cross-modality;uncertainty;robustness
| null | 2.666667 | null | null |
iclr
| 0.944911 | 0.944911 | null |
main
| 6.333333 |
5;6;8
|
3;3;4
| null |
Robust Cross-Modal Semi-supervised Few Shot Learning
| null | null | 3.333333 | 2.333333 |
Reject
|
2;2;3
|
2;3;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
1;3;3;2
| null | null | null |
hard-label attacks;adversarial machine learning;generalization
| null | 1.75 | null | null |
iclr
| -0.870388 | 0.870388 | null |
main
| 4.5 |
3;5;5;5
|
1;3;2;3
| null |
Less is More: Dimension Reduction Finds On-Manifold Adversarial Examples in Hard-Label Attacks
| null | null | 2.25 | 2.75 |
Reject
|
4;2;3;2
|
1;0;3;3
|
null |
UC San Diego; Carnegie Mellon University; University of Southern California
|
2022
| 3.333333 |
https://iclr.cc/virtual/2022/poster/6524; None
| null | 0 | null | null | null |
3;3;4
| null |
Junxian He, Chunting Zhou, Xuezhe Ma, Taylor Berg-Kirkpatrick, Graham Neubig
|
https://iclr.cc/virtual/2022/poster/6524
|
parameter-efficient transfer learning;unified view;natural language processing
| null | 3.333333 | null |
https://openreview.net/forum?id=0RDcd5Axok
|
iclr
| 0.866025 | 0.5 | null |
main
| 8.666667 |
8;8;10
|
3;4;4
|
https://iclr.cc/virtual/2022/poster/6524
|
Towards a Unified View of Parameter-Efficient Transfer Learning
|
https://github.com/jxhe/unify-parameter-efficient-tuning
| null | 3.666667 | 4 |
Spotlight
|
4;3;5
|
3;3;4
|
null |
Baidu Research, 1195 Bordeaux Dr, Sunnyvale, CA 94089, USA
|
2022
| 2.25 |
https://iclr.cc/virtual/2022/poster/6093; None
| null | 0 | null | null | null |
2;2;2;3
| null |
Xingyu Cai, Jiahong Yuan, Yuchen Bian, Guangxu Xun, Jiaji Huang, Kenneth Church
|
https://iclr.cc/virtual/2022/poster/6093
|
CTC;wild cards;dynamic programing;partial alignment
| null | 2.75 | null |
https://openreview.net/forum?id=0RqDp8FCW5Z
|
iclr
| 0 | 0 | null |
main
| 6 |
6;6;6;6
|
4;3;4;3
|
https://iclr.cc/virtual/2022/poster/6093
|
W-CTC: a Connectionist Temporal Classification Loss with Wild Cards
| null | null | 3.5 | 4.25 |
Poster
|
5;4;4;4
|
2;3;3;3
|
null | null |
2022
| 2.333333 | null | null | 0 | null | null | null |
3;2;2
| null | null | null |
additive manufacturing;closed-loop;reinforcement learning;in-process
| null | 2.333333 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
5;5;5
|
3;4;2
| null |
Closed-Loop Control of Additive Manufacturing via Reinforcement Learning
| null | null | 3 | 3.333333 |
Reject
|
3;3;4
|
2;2;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;2;3
| null | null | null |
Deep learning;uncertainty estimation;out-of-distribution detection
| null | 2.5 | null | null |
iclr
| 0.816497 | 0.816497 | null |
main
| 6 |
5;5;6;8
|
3;3;4;4
| null |
Deep Classifiers with Label Noise Modeling and Distance Awareness
| null | null | 3.5 | 3.5 |
Reject
|
3;3;4;4
|
2;2;3;3
|
null | null |
2022
| 2.75 | null | null | 0 | null | null | null |
2;3;3;3
| null | null | null |
Deep Probabilistic Programming Languages;Probabilistic Circuits;Neuro-Symbolic Computations
| null | 2.5 | null | null |
iclr
| -0.992278 | 0.800641 | null |
main
| 5.5 |
3;5;6;8
|
3;3;3;4
| null |
SLASH: Embracing Probabilistic Circuits into Neural Answer Set Programming
| null | null | 3.25 | 3.5 |
Reject
|
5;4;3;2
|
2;2;3;3
|
null |
Georgia Institute of Technology; DeepMind
|
2022
| 2.25 |
https://iclr.cc/virtual/2022/poster/6390; None
| null | 0 | null | null | null |
2;2;2;3
| null |
Shantanu Thakoor, Corentin Tallec, Mohammad Gheshlaghi Azar, Mehdi Azabou, Eva Dyer, Remi Munos, Petar Veličković, Michal Valko
|
https://iclr.cc/virtual/2022/poster/6390
| null | null | 3.25 | null |
https://openreview.net/forum?id=0UXT6PpRpW
|
iclr
| 0.662266 | 0.688247 | null |
main
| 6.25 |
5;6;6;8
|
3;3;4;4
|
https://iclr.cc/virtual/2022/poster/6390
|
Large-Scale Representation Learning on Graphs via Bootstrapping
| null | null | 3.5 | 4.5 |
Poster
|
3;5;5;5
|
4;3;3;3
|
null | null |
2022
| 2.25 | null | null | 0 | null | null | null |
2;2;3;2
| null | null | null |
multi-agent reinforcement learning
| null | 2.25 | null | null |
iclr
| -1 | -0.57735 | null |
main
| 4 |
3;3;5;5
|
3;3;3;2
| null |
Online Tuning for Offline Decentralized Multi-Agent Reinforcement Learning
| null | null | 2.75 | 4.5 |
Reject
|
5;5;4;4
|
2;2;3;2
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.