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values |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Residual neural networks;Recurrent neural networks;Computer vision
| null | 0 | null | null |
iclr
| 0.333333 | 0 | null |
main
| 5.25 |
5;5;5;6
| null | null |
Iterative convergent computation is not a useful inductive bias for ResNets
| null | null | 0 | 3.75 |
Reject
|
4;3;4;4
| null |
null |
Stanford University; Intel Labs; Columbia University
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/2866; None
| null | 0 | null | null | null | null | null |
Cory Stephenson, Suchismita Padhy, Abhinav Ganesh, Yue Hui, Hanlin Tang, SueYeon Chung
|
https://iclr.cc/virtual/2021/poster/2866
|
deep learning theory;representation learning;statistical physics methods;double descent
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 7 |
7;7;7;7
| null |
https://iclr.cc/virtual/2021/poster/2866
|
On the geometry of generalization and memorization in deep neural networks
| null | null | 0 | 3.5 |
Poster
|
4;3;4;3
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
GAN;segmentation;unsupervised
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
4;5;5;6
| null | null |
Big GANs Are Watching You: Towards Unsupervised Object Segmentation with Off-the-Shelf Generative Models
|
https://github.com/gans-are-watching/iclr2021_submit
| null | 0 | 4 |
Withdraw
|
4;4;4;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Disentanglement;representations;GANs
| null | 0 | null | null |
iclr
| -0.755929 | 0 | null |
main
| 5.666667 |
4;6;7
| null | null |
On Disentangled Representations Extracted from Pretrained GANs
|
https://bit.ly/3ipb6dW
| null | 0 | 3.666667 |
Reject
|
4;4;3
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
novel recurrent neural architectures;learning representations of outputs or states
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 0 | null | null | null |
Time Adaptive Recurrent Neural Network
| null | null | 0 | 0 |
Withdraw
| null | null |
null |
Nanyang Technological University; Amazon AI; Mila, Polytechnique Montreal
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/3002; None
| null | 0 | null | null | null | null | null |
Alvin Chan, Yew-Soon Ong, Bill Pung, Aston Zhang, Jie Fu
|
https://iclr.cc/virtual/2021/poster/3002
|
Language modeling;text generation;controlled generation;self-supervised learning
| null | 0 | null | null |
iclr
| -0.717137 | 0 | null |
main
| 6.25 |
4;6;7;8
| null |
https://iclr.cc/virtual/2021/poster/3002
|
CoCon: A Self-Supervised Approach for Controlled Text Generation
|
https://github.com/alvinchangw/COCONICLR2021
| null | 0 | 4 |
Poster
|
5;4;3;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
embedding transfer;knowledge distillation;deep metric learning;representation learning
| null | 0 | null | null |
iclr
| -0.420084 | 0 | null |
main
| 5.166667 |
4;5;5;5;6;6
| null | null |
Embedding Transfer via Smooth Contrastive Loss
| null | null | 0 | 4 |
Withdraw
|
4;4;5;4;4;3
| null |
null |
Department of Electrical Engineering, Stanford University
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/2630; None
| null | 0 | null | null | null | null | null |
Arda Sahiner, Morteza Mardani, Batu Ozturkler, Mert Pilanci, John M Pauly
|
https://iclr.cc/virtual/2021/poster/2630
|
neural networks;image reconstruction;denoising;interpretability;robustness;neural reconstruction;convex duality;inverse problems;sparsity;convex optimization
| null | 0 | null | null |
iclr
| 0.889297 | 0 | null |
main
| 6.25 |
4;6;6;9
| null |
https://iclr.cc/virtual/2021/poster/2630
|
Convex Regularization behind Neural Reconstruction
| null | null | 0 | 4.25 |
Poster
|
4;4;4;5
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
phrase transformer;logical form;semantic parsing;neural machine translation;meaning representation
| null | 0 | null | null |
iclr
| 0.090909 | 0 | null |
main
| 4.5 |
3;3;5;7
| null | null |
PhraseTransformer: Self-Attention using Local Context for Semantic Parsing
| null | null | 0 | 4.25 |
Reject
|
3;5;5;4
| null |
null |
Australian National University, Data61 (CSIRO); Mohamed bin Zayed University of AI, Australian National University; Australian National University; Mohamed bin Zayed University of AI
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/2764; None
| null | 0 | null | null | null | null | null |
Sameera Ramasinghe, Kanchana Ranasinghe, Salman Khan, Nick Barnes, Stephen Gould
|
https://iclr.cc/virtual/2021/poster/2764
|
Multimodal Spaces;Conditional Generation;Generative Modeling
| null | 0 | null | null |
iclr
| 0.96225 | 0 | null |
main
| 7.5 |
6;7;7;10
| null |
https://iclr.cc/virtual/2021/poster/2764
|
Conditional Generative Modeling via Learning the Latent Space
|
https://github.com/samgregoost/cGML
| null | 0 | 3.5 |
Poster
|
3;3;3;5
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null | null | null | 0 | null | null |
iclr
| -1 | 0 | null |
main
| 4.666667 |
4;5;5
| null | null |
Image Animation with Refined Masking
| null | null | 0 | 4.333333 |
Withdraw
|
5;4;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Compositionality
| null | 0 | null | null |
iclr
| -0.87831 | 0 | null |
main
| 3.25 |
1;3;4;5
| null | null |
Gradient Descent Resists Compositionality
| null | null | 0 | 3.25 |
Reject
|
4;3;3;3
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Multi-agent reinforcement learning;Fitted Q-iteration;Value factorization;Credit assignment
| null | 0 | null | null |
iclr
| -0.333333 | 0 | null |
main
| 5.25 |
5;5;5;6
| null | null |
Towards Understanding Linear Value Decomposition in Cooperative Multi-Agent Q-Learning
| null | null | 0 | 4.25 |
Reject
|
4;5;4;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Graph neural network;Attention mechanism;Reinforcement learning;Multi-robotic task allocation
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 5.333333 |
4;5;7
| null | null |
Learning to Solve Multi-Robot Task Allocation with a Covariant-Attention based Neural Architecture
| null | null | 0 | 4 |
Reject
|
4;4;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Dynamical Isometry;Gradient Propagation;Deep Learning;Small-world Networks;Efficient Inference
| null | 0 | null | null |
iclr
| 0.27735 | 0 | null |
main
| 3.666667 |
2;3;6
| null | null |
On the relationship between topology and gradient propagation in deep networks
| null | null | 0 | 3.666667 |
Withdraw
|
4;3;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null | null | null | 0 | null | null |
iclr
| -0.57735 | 0 | null |
main
| 5.5 |
4;4;7;7
| null | null |
A priori guarantees of finite-time convergence for Deep Neural Networks
| null | null | 0 | 3.5 |
Reject
|
5;3;3;3
| null |
null |
Deepmind; Waverly; Google Research, Brain Team; Mila, University of Montreal; IIT BHU, Varanasi; UC Berkeley
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/2917; None
| null | 0 | null | null | null | null | null |
Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Charles Blundell, Sergey Levine, Yoshua Bengio, Michael Mozer
|
https://iclr.cc/virtual/2021/poster/2917
|
procedural knowledge;declarative knowledge;Systematicity
| null | 0 | null | null |
iclr
| 0.774597 | 0 | null |
main
| 6.5 |
5;6;7;8
| null |
https://iclr.cc/virtual/2021/poster/2917
|
Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments
| null | null | 0 | 3.75 |
Poster
|
3;4;4;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
nonconvex;optimization;stochastic;sampling;MCMC;majorization-minimization
| null | 0 | null | null |
iclr
| -0.377871 | 0 | null |
main
| 5.4 |
3;5;6;6;7
| null | null |
MISSO: Minimization by Incremental Stochastic Surrogate Optimization for Large Scale Nonconvex and Nonsmooth Problems
| null | null | 0 | 3.2 |
Reject
|
5;1;3;4;3
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Off-policy selection;reinforcement learning;Bayesian inference
| null | 0 | null | null |
iclr
| -0.5 | 0 | null |
main
| 5.666667 |
5;6;6
| null | null |
Offline policy selection under Uncertainty
| null | null | 0 | 3.666667 |
Reject
|
4;4;3
| null |
null |
Microsoft Corporation, Redmond, WA 98052, USA
|
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
HYPERPARAMETER OPTIMIZATION;COST
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 6.333333 |
6;6;7
| null | null |
ECONOMIC HYPERPARAMETER OPTIMIZATION WITH BLENDED SEARCH STRATEGY
| null | null | 0 | 4 |
Poster
|
5;3;4
| null |
null |
Carnegie Mellon University; Carnegie Mellon University, Bosch Center for Artificial Intelligence
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/3308; None
| null | 0 | null | null | null | null | null |
Chirag Pabbaraju, Ezra Winston, Zico Kolter
|
https://iclr.cc/virtual/2021/poster/3308
|
deep equilibrium models;Lipschitz constants
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 5.8 |
5;5;6;6;7
| null |
https://iclr.cc/virtual/2021/poster/3308
|
Estimating Lipschitz constants of monotone deep equilibrium models
| null | null | 0 | 4 |
Poster
|
4;4;5;3;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
adversarial defense;distribution alignment;high-level computer vision task
| null | 0 | null | null |
iclr
| -0.447214 | 0 | null |
main
| 4.5 |
3;4;5;6
| null | null |
General Adversarial Defense via Pixel Level and Feature Level Distribution Alignment
| null | null | 0 | 4.5 |
Withdraw
|
5;4;5;4
| null |
null |
Google Research, Carnegie Mellon University; Google Research
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/3100; None
| null | 0 | null | null | null | null | null |
Paul Pu Liang, Manzil Zaheer, Yuan Wang, Amr Ahmed
|
https://iclr.cc/virtual/2021/poster/3100
|
sparse embeddings;large vocabularies;text classification;language modeling;recommendation systems
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 6 |
5;6;7
| null |
https://iclr.cc/virtual/2021/poster/3100
|
Anchor & Transform: Learning Sparse Embeddings for Large Vocabularies
|
https://github.com/pliang279/sparse_discrete
| null | 0 | 4 |
Poster
|
4;4;4
| null |
null |
Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA; School of Computer Science, Carnegie Mellon University, Pittsburgh, PA
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/2537; None
| null | 0 | null | null | null | null | null |
Marisa Kirisame, Steven S. Lyubomirsky, Altan Haan, Jennifer Brennan, Mike He, Jared G Roesch, Tianqi Chen, Zachary Tatlock
|
https://iclr.cc/virtual/2021/poster/2537
|
Rematerialization;Memory-saving;Runtime Systems;Checkpointing
| null | 0 | null | null |
iclr
| 0.707107 | 0 | null |
main
| 6.5 |
6;6;7;7
| null |
https://iclr.cc/virtual/2021/poster/2537
|
Dynamic Tensor Rematerialization
| null | null | 0 | 4 |
Spotlight
|
4;3;4;5
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null | null | null | 0 | null | null |
iclr
| -0.507093 | 0 | null |
main
| 4.75 |
3;4;5;7
| null | null |
Human-interpretable model explainability on high-dimensional data
| null | null | 0 | 3.5 |
Reject
|
4;3;4;3
| null |
null |
University of Waterloo
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/2859; None
| null | 0 | null | null | null | null | null |
Nils Lukas, Yuxuan Zhang, Florian Kerschbaum
|
https://iclr.cc/virtual/2021/poster/2859
|
Fingerprinting;Adversarial Examples;Transferability;Conferrability
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 6.25 |
6;6;6;7
| null |
https://iclr.cc/virtual/2021/poster/2859
|
Deep Neural Network Fingerprinting by Conferrable Adversarial Examples
| null | null | 0 | 3 |
Spotlight
|
2;3;4;3
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
BERT;deep learning;multi-span answer;question-answering;SQuAD;transformers
| null | 0 | null | null |
iclr
| -0.956183 | 0 | null |
main
| 3.25 |
1;3;4;5
| null | null |
MULTI-SPAN QUESTION ANSWERING USING SPAN-IMAGE NETWORK
| null | null | 0 | 4 |
Reject
|
5;4;4;3
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Federated Learning;Machine Learning;End-to-End Learning;Artificial Intelligence
| null | 0 | null | null |
iclr
| -0.816497 | 0 | null |
main
| 4 |
2;4;4;6
| null | null |
End-to-End on-device Federated Learning: A case study
| null | null | 0 | 4.25 |
Reject
|
5;4;4;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Transformer;Question Answering
| null | 0 | null | null |
iclr
| -0.781661 | 0 | null |
main
| 4.75 |
2;5;6;6
| null | null |
Cluster-Former: Clustering-based Sparse Transformer for Question Answering
| null | null | 0 | 3.75 |
Reject
|
5;3;3;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
adversarial attack;graph neural networks;spatiotemporal forecasting
| null | 0 | null | null |
iclr
| -0.333333 | 0 | null |
main
| 5 |
4;4;4;8
| null | null |
One Vertex Attack on Graph Neural Networks-based Spatiotemporal Forecasting
| null | null | 0 | 3.5 |
Reject
|
3;3;5;3
| null |
null |
Salesforce Research; Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign
|
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Neural text decoding;sampling algorithms;cross-entropy;repetitions;incoherence
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 6.333333 |
6;6;7
| null | null |
MIROSTAT: A NEURAL TEXT DECODING ALGORITHM THAT DIRECTLY CONTROLS PERPLEXITY
| null | null | 0 | 4 |
Poster
|
3;5;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
SGD;regularization;generalization;statistical mechanics;thermophoresis
| null | 0 | null | null |
iclr
| 0.693375 | 0 | null |
main
| 4.666667 |
3;4;7
| null | null |
Implicit Regularization of SGD via Thermophoresis
| null | null | 0 | 2.666667 |
Reject
|
2;3;3
| null |
null |
University of Toronto, Vector Institute, Nvidia; Layer 6 AI
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/3171; None
| null | 0 | null | null | null | null | null |
Panteha Naderian, Gabriel Loaiza-Ganem, Harry Braviner, Anthony Caterini, Jesse C Cresswell, Tong Li, Animesh Garg
|
https://iclr.cc/virtual/2021/poster/3171
|
reinforcement learning;goal reaching;Q-learning
| null | 0 | null | null |
iclr
| 0.57735 | 0 |
https://sites.google.com/view/learning-cae/
|
main
| 5.75 |
5;6;6;6
| null |
https://iclr.cc/virtual/2021/poster/3171
|
C-Learning: Horizon-Aware Cumulative Accessibility Estimation
|
https://github.com/layer6ai-labs/CAE
| null | 0 | 3.5 |
Poster
|
3;4;3;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
reinforcement learning;multi-goal task;experience replay
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 3.5 |
3;3;4;4
| null | null |
Hindsight Curriculum Generation Based Multi-Goal Experience Replay
| null | null | 0 | 4 |
Reject
|
4;4;4;4
| null |
null |
Department of Computing, Imperial College London, UK
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/3166; None
| null | 0 | null | null | null | null | null |
Konstantinos Vougioukas, Stavros Petridis, Maja Pantic
|
https://iclr.cc/virtual/2021/poster/3166
|
Generative Modelling;Domain Translation;Conditional GANs;Energy-Based GANs
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 7 |
7;7;7
| null |
https://iclr.cc/virtual/2021/poster/3166
|
DINO: A Conditional Energy-Based GAN for Domain Translation
|
https://github.com/DinoMan/DINO
| null | 0 | 2.333333 |
Poster
|
2;2;3
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Continuous action space;Deep learning;Multi-scale change point detection;Off-policy evaluation
| null | 0 | null | null |
iclr
| -0.927173 | 0 | null |
main
| 6.25 |
5;6;6;8
| null | null |
Deep Jump Q-Evaluation for Offline Policy Evaluation in Continuous Action Space
| null | null | 0 | 2.5 |
Reject
|
3;3;3;1
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
multilingual representations;sentence embeddings
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 5.5 |
4;5;6;7
| null | null |
Universal Sentence Representations Learning with Conditional Masked Language Model
| null | null | 0 | 4 |
Reject
|
4;4;4;4
| null |
null |
University of Connecticut; MIT-IBM Watson AI Lab, IBM Research
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/2800; None
| null | 0 | null | null | null | null | null |
Chao Shang, Jie Chen, Jinbo Bi
|
https://iclr.cc/virtual/2021/poster/2800
|
Time series forecasting;graph neural network;graph structure learning
| null | 0 | null | null |
iclr
| -0.188982 | 0 | null |
main
| 5.666667 |
4;6;7
| null |
https://iclr.cc/virtual/2021/poster/2800
|
Discrete Graph Structure Learning for Forecasting Multiple Time Series
| null | null | 0 | 3.666667 |
Poster
|
4;3;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null | null | null | 0 | null | null |
iclr
| 0.301511 | 0 |
Not provided
|
main
| 4.75 |
4;4;5;6
| null | null |
Self-supervised Temporal Learning
|
Not provided
| null | 0 | 4.5 |
Withdraw
|
5;4;4;5
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Supervised Representation Learning;Deep Neural Networks;Generalization;Early Stopping
| null | 0 | null | null |
iclr
| -0.57735 | 0 | null |
main
| 5.5 |
5;5;5;7
| null | null |
Early Stopping by Gradient Disparity
| null | null | 0 | 3.5 |
Reject
|
4;3;4;3
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
model robustness;data augmentation;adversarial training;image quality;autonomous driving;benchmark
| null | 0 | null | null |
iclr
| 0.522233 | 0 | null |
main
| 4.5 |
4;4;4;6
| null | null |
Driving through the Lens: Improving Generalization of Learning-based Steering using Simulated Adversarial Examples
| null | null | 0 | 4.25 |
Reject
|
3;4;5;5
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Neural ODE;DOPRI
| null | 0 | null | null |
iclr
| -0.174078 | 0 | null |
main
| 5.25 |
4;5;6;6
| null | null |
DISE: Dynamic Integrator Selection to Minimize Forward Pass Time in Neural ODEs
| null | null | 0 | 3.25 |
Reject
|
3;4;3;3
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Recommender Systems;Recurrent Neural Networks;Deep Learning
| null | 0 | null | null |
iclr
| 0.57735 | 0 | null |
main
| 4.5 |
4;4;5;5
| null | null |
Recurrent Exploration Networks for Recommender Systems
| null | null | 0 | 3.25 |
Reject
|
3;3;4;3
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Meta Learning;Hyperparameter Optimization;Transfer Learning
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 5.25 |
5;5;5;6
| null | null |
Hyperparameter Transfer Across Developer Adjustments
| null | null | 0 | 4 |
Reject
|
4;4;4;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Riemannian optimization;acceleration;first-order methods
| null | 0 | null | null |
iclr
| -0.480384 | 0 | null |
main
| 5.4 |
4;5;5;6;7
| null | null |
Acceleration in Hyperbolic and Spherical Spaces
| null | null | 0 | 2.2 |
Reject
|
2;4;2;2;1
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Invariance;Convolutional Networks;Translation;Internal Representations
| null | 0 | null | null |
iclr
| 0.866025 | 0 | null |
main
| 4.333333 |
4;4;5
| null | null |
Convolutional Neural Networks are not invariant to translation, but they can learn to be
| null | null | 0 | 4 |
Reject
|
3;4;5
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Unsupervised dimension reduction;sufficient dimension reduction;alternating scheme;Fourier transform;maximum mean discrepancy;Wasserstein distance;positive definite functions;Bochner’s theorem
| null | 0 | null | null |
iclr
| -0.327327 | 0 | null |
main
| 5.333333 |
4;5;7
| null | null |
Dimension reduction as an optimization problem over a set of generalized functions
| null | null | 0 | 3 |
Reject
|
4;2;3
| null |
null |
N/A
|
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Federated learning;lossy broadcasting
| null | 0 | null | null |
iclr
| -0.333333 | 0 | null |
main
| 5.25 |
5;5;5;6
| null | null |
Federated Learning With Quantized Global Model Updates
| null | null | 0 | 3.25 |
Reject
|
3;3;4;3
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null | null | null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 5 |
4;5;5;6
| null | null |
Unsupervised Word Alignment via Cross-Lingual Contrastive Learning
|
https://github.com/ICLR20anonymous/mirroralign
| null | 0 | 4.25 |
Withdraw
|
4;5;4;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Interpretability;Feature Attribution;Neural Network Pruning;Critical Paths
| null | 0 | null | null |
iclr
| 0.944911 | 0 | null |
main
| 4.666667 |
4;4;6
| null | null |
On Sparse Critical Paths of Neural Response
| null | null | 0 | 3.333333 |
Withdraw
|
3;2;5
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Explainable Reinforcement Learning;Decision Tree;Matrix Factorization
| null | 0 | null | null |
iclr
| -0.894427 | 0 | null |
main
| 4.5 |
4;4;5;5
| null | null |
CDT: Cascading Decision Trees for Explainable Reinforcement Learning
| null | null | 0 | 3.5 |
Reject
|
5;4;2;3
| null |
null |
Department of Computer Science and Engineering, University of California, Santa Cruz, Santa Cruz, CA 95060, USA
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/2763; None
| null | 0 | null | null | null | null | null |
Jiaheng Wei, Yang Liu
|
https://iclr.cc/virtual/2021/poster/2763
|
$f-$divergence;robustness;learning with noisy labels
| null | 0 | null | null |
iclr
| -0.333333 | 0 | null |
main
| 6.75 |
6;7;7;7
| null |
https://iclr.cc/virtual/2021/poster/2763
|
When Optimizing $f$-Divergence is Robust with Label Noise
|
https://github.com/UCSC-REAL/Robust-f-divergence-measures
| null | 0 | 2.75 |
Poster
|
3;3;3;2
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Dynamic Self-Supervised Learning;Commonsense Reasoning
| null | 0 | null | null |
iclr
| -0.816497 | 0 | null |
main
| 4 |
3;4;4;5
| null | null |
Erasure for Advancing: Dynamic Self-Supervised Learning for Commonsense Reasoning
| null | null | 0 | 3.25 |
Withdraw
|
4;3;3;3
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
vision-language pre-training;cross-modal representation;semantic gap
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 4.5 |
4;4;5;5
| null | null |
SemVLP: Vision-Language Pre-training by Aligning Semantics at Multiple Levels
| null | null | 0 | 3.5 |
Withdraw
|
3;4;3;4
| null |
null |
KAIST; KAIST, AITRICS
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/2762; None
| null | 0 | null | null | null | null | null |
Seanie Lee, Dong Bok Lee, Sung Ju Hwang
|
https://iclr.cc/virtual/2021/poster/2762
|
conditional text generation;contrastive learning
| null | 0 | null | null |
iclr
| -0.174078 | 0 | null |
main
| 5.25 |
4;5;6;6
| null |
https://iclr.cc/virtual/2021/poster/2762
|
Contrastive Learning with Adversarial Perturbations for Conditional Text Generation
| null | null | 0 | 3.25 |
Poster
|
3;4;3;3
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
dynamical systems;polynomial neural networks;anomaly detection
| null | 0 | null | null |
iclr
| -0.5 | 0 | null |
main
| 4.333333 |
4;4;5
| null | null |
Anomaly detection in dynamical systems from measured time series
| null | null | 0 | 4.333333 |
Reject
|
4;5;4
| null |
null |
KAIST, Republic of Korea
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/2604; None
| null | 0 | null | null | null | null | null |
Dongkwan Kim, Alice Oh
|
https://iclr.cc/virtual/2021/poster/2604
|
Graph Neural Network;Attention Mechanism;Self-supervised Learning
| null | 0 | null | null |
iclr
| 0.223607 | 0 | null |
main
| 6 |
4;5;7;8
| null |
https://iclr.cc/virtual/2021/poster/2604
|
How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision
| null | null | 0 | 4 |
Poster
|
4;4;3;5
| null |
null |
Zalando Research
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/3117; None
| null | 0 | null | null | null | null | null |
Kashif Rasul, Abdul-Saboor Sheikh, Ingmar Schuster, Urs Bergmann, Roland Vollgraf
|
https://iclr.cc/virtual/2021/poster/3117
|
time series;normalizing flows;attention;probabilistic multivariate forecasting
| null | 0 | null | null |
iclr
| 0.760886 | 0 | null |
main
| 7.25 |
6;7;7;9
| null |
https://iclr.cc/virtual/2021/poster/3117
|
Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows
| null | null | 0 | 4.25 |
Spotlight
|
3;5;4;5
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Data Privacy;Information-theoretic Privacy;DNN Privacy;Trusted Execution Environment;Intel SGX
| null | 0 | null | null |
iclr
| 0.301511 | 0 | null |
main
| 4.25 |
3;4;5;5
| null | null |
DarKnight: A Data Privacy Scheme for Training and Inference of Deep Neural Networks
| null | null | 0 | 3.5 |
Reject
|
3;4;4;3
| null |
null |
Department of Computational Linguistics, University of Zurich; School of Informatics, University of Edinburgh; Google Research
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/3193; None
| null | 0 | null | null | null | null | null |
Biao Zhang, Ankur Bapna, Rico Sennrich, Orhan Firat
|
https://iclr.cc/virtual/2021/poster/3193
|
language-specific modeling;conditional computation;multilingual translation;multilingual transformer
| null | 0 | null | null |
iclr
| -0.426401 | 0 | null |
main
| 7.75 |
7;7;8;9
| null |
https://iclr.cc/virtual/2021/poster/3193
|
Share or Not? Learning to Schedule Language-Specific Capacity for Multilingual Translation
|
https://github.com/bzhangGo/zero/tree/iclr2021_clsr
| null | 0 | 4 |
Oral
|
4;4;5;3
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
deep subspace clustering;convolutional neural networks;self-supervised learning;correntropy;generalization;robustness
| null | 0 | null | null |
iclr
| 0.5 | 0 | null |
main
| 4.333333 |
3;5;5
| null | null |
Subspace Clustering via Robust Self-Supervised Convolutional Neural Network
| null | null | 0 | 4.333333 |
Reject
|
4;4;5
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
deep learning;language model;transformer network;multi-scale transformer network;natural language processing;transformer-xl
| null | 0 | null | null |
iclr
| 0.132453 | 0 | null |
main
| 5.25 |
4;5;5;7
| null | null |
Transformer-QL: A Step Towards Making Transformer Network Quadratically Large
| null | null | 0 | 3.75 |
Reject
|
4;3;4;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Reinforcement Learning;Multi-agent Reinforcement Learning
| null | 0 | null | null |
iclr
| -0.09759 | 0 | null |
main
| 5.25 |
3;5;6;7
| null | null |
PettingZoo: Gym for Multi-Agent Reinforcement Learning
| null | null | 0 | 3.25 |
Reject
|
3;4;3;3
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Domain Adaptation;Adversarial Learning;Transfer Learning;Neural Networks;Deep Learning
| null | 0 | null | null |
iclr
| -0.57735 | 0 | null |
main
| 4.75 |
4;5;5;5
| null | null |
f-Domain-Adversarial Learning: Theory and Algorithms for Unsupervised Domain Adaptation with Neural Networks
| null | null | 0 | 4.5 |
Reject
|
5;4;5;4
| null |
null |
N/A
|
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
federated learning;secure machine learning;backdoor attacks;inference attacks;data privacy
| null | 0 | null | null |
iclr
| 1 | 0 | null |
main
| 5.5 |
4;6;6;6
| null | null |
BAFFLE: TOWARDS RESOLVING FEDERATED LEARNING’S DILEMMA - THWARTING BACKDOOR AND INFERENCE ATTACKS
| null | null | 0 | 3.75 |
Reject
|
3;4;4;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Incremental Learning;Unsupervised Learning;Continual Learning;Novelty Detection;Out-of-Distribution Detection
| null | 0 | null | null |
iclr
| 0.738549 | 0 | null |
main
| 4 |
3;3;4;6
| null | null |
Unsupervised Class-Incremental Learning through Confusion
| null | null | 0 | 3.25 |
Reject
|
3;2;4;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
domain generalization;uncertainty assessment;data augmentation;Bayesian meta-learning
| null | 0 | null | null |
iclr
| -0.816497 | 0 | null |
main
| 5 |
3;5;6;6
| null | null |
Uncertain Out-of-Domain Generalization
| null | null | 0 | 3.5 |
Withdraw
|
4;4;3;3
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null | null | null | 0 | null | null |
iclr
| -0.936586 | 0 | null |
main
| 4.25 |
3;4;4;6
| null | null |
Skinning a Parameterization of Three-Dimensional Space for Neural Network Cloth
| null | null | 0 | 3 |
Reject
|
4;4;3;1
| null |
null |
University of Amsterdam, University of Edinburgh
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/2852; None
| null | 0 | null | null | null | null | null |
Michael Schlichtkrull, Nicola De Cao, Ivan Titov
|
https://iclr.cc/virtual/2021/poster/2852
|
Graph neural networks;interpretability;sparse stochastic gates;semantic role labeling;question answering
| null | 0 | null | null |
iclr
| -0.333333 | 0 | null |
main
| 6.75 |
6;7;7;7
| null |
https://iclr.cc/virtual/2021/poster/2852
|
Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking
| null | null | 0 | 3.75 |
Spotlight
|
4;4;4;3
| null |
null |
MIT-IBM Watson AI Lab, IBM Research; Princeton Neuroscience Institute, Princeton University
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/2695; None
| null | 0 | null | null | null | null | null |
Dmitry Krotov, John J Hopfield
|
https://iclr.cc/virtual/2021/poster/2695
|
associative memory;Hopfield networks;modern Hopfield networks;neuroscience
| null | 0 | null | null |
iclr
| -0.816497 | 0 | null |
main
| 7 |
6;7;7;8
| null |
https://iclr.cc/virtual/2021/poster/2695
|
Large Associative Memory Problem in Neurobiology and Machine Learning
| null | null | 0 | 3.25 |
Poster
|
4;3;3;3
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
minimax optimization;nonconvex;variance reduction
| null | 0 | null | null |
iclr
| -0.301511 | 0 | null |
main
| 5.25 |
4;5;6;6
| null | null |
Enhanced First and Zeroth Order Variance Reduced Algorithms for Min-Max Optimization
| null | null | 0 | 4 |
Reject
|
5;3;5;3
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Reinforcement Learning
| null | 0 | null | null |
iclr
| -0.57735 | 0 | null |
main
| 5 |
4;4;5;5;7
| null | null |
Mixture of Step Returns in Bootstrapped DQN
| null | null | 0 | 4 |
Reject
|
4;4;5;4;3
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Data Efficiency;Small Sample Size;Data Dimensionality;Image Background
| null | 0 | null | null |
iclr
| 0.301511 | 0 | null |
main
| 4.25 |
3;4;5;5
| null | null |
The Foes of Neural Network’s Data Efficiency Among Unnecessary Input Dimensions
| null | null | 0 | 3.5 |
Withdraw
|
3;4;3;4
| null |
null |
Shanghai Jiao Tong University; Key Lab. of Machine Perception (MoE), School of EECS, Peking University, Beijing, China
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/2888; None
| null | 0 | null | null | null | null | null |
Xin Wang, Jie Ren, Shuyun Lin, Xiangming Zhu, Yisen Wang, Quanshi Zhang
|
https://iclr.cc/virtual/2021/poster/2888
|
Adversarial Learning;Interpretability;Adversarial Transferability
| null | 0 | null | null |
iclr
| 0.97714 | 0 | null |
main
| 6.75 |
5;6;6;10
| null |
https://iclr.cc/virtual/2021/poster/2888
|
A Unified Approach to Interpreting and Boosting Adversarial Transferability
|
https://github.com/xherdan76/A-Unified-Approach-to-Interpreting-and-Boosting-Adversarial-Transferability
| null | 0 | 3.25 |
Poster
|
3;3;3;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
nlg;paraphrasing;unsupervised;decoding;language modeling;generation
| null | 0 | null | null |
iclr
| 0.866025 | 0 | null |
main
| 5.333333 |
5;5;6
| null | null |
Reflective Decoding: Unsupervised Paraphrasing and Abductive Reasoning
| null | null | 0 | 4 |
Withdraw
|
3;4;5
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Neural Architecture Search;Segmentation;Computer Vision
| null | 0 | null | null |
iclr
| 1 | 0 | null |
main
| 3.666667 |
3;4;4
| null | null |
Bractivate: Dendritic Branching in Medical Image Segmentation Neural Architecture Search
|
https://tinyurl.com/bractivate
| null | 0 | 3.666667 |
Reject
|
3;4;4
| null |
null |
Machine Learning Research Lab, Volkswagen Group, Munich, Germany
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/2879; None
| null | 0 | null | null | null | null | null |
Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt, Justin Bayer
|
https://iclr.cc/virtual/2021/poster/2879
|
Generative models;Bayesian inference;Variational inference;SLAM;Deep learning
| null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 6.25 |
6;6;6;7
| null |
https://iclr.cc/virtual/2021/poster/2879
|
Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF
| null | null | 0 | 4 |
Poster
|
4;5;3;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Deep Neural Networks;Knowledge Distillation;Natural Language Processing
| null | 0 | null | null |
iclr
| -0.632456 | 0 | null |
main
| 4.5 |
3;4;5;6
| null | null |
Improved knowledge distillation by utilizing backward pass knowledge in neural networks
| null | null | 0 | 4 |
Withdraw
|
5;4;3;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
domain adaptation;self-labeling;chemical graph recognition
| null | 0 | null | null |
iclr
| 0.57735 | 0 | null |
main
| 4.5 |
4;4;5;5
| null | null |
Self-Labeling of Fully Mediating Representations by Graph Alignment
| null | null | 0 | 3.75 |
Reject
|
4;3;4;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
meta learning;plasticity;local learning;deep learning;machine learning;neural networks;RNNs;backpropagation;perceptron;evolution;adversarial examples
| null | 0 | null | null |
iclr
| -0.96225 | 0 | null |
main
| 5.75 |
4;5;7;7
| null | null |
Learning with Plasticity Rules: Generalization and Robustness
| null | null | 0 | 3.5 |
Reject
|
4;4;3;3
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
few-shot learning;continual learning;benchmark
| null | 0 | null | null |
iclr
| 0.870388 | 0 | null |
main
| 5.25 |
4;5;6;6
| null | null |
Defining Benchmarks for Continual Few-Shot Learning
| null | null | 0 | 3.75 |
Reject
|
3;4;4;4
| null |
null |
Department of Statistics, University of British Columbia; Department of Statistics, University of Michigan; School of Information and Department of EECS, University of Michigan; School of Information, University of Michigan
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/2572; None
| null | 0 | null | null | null | null | null |
Jiaqi Ma, Bo Chang, Xuefei Zhang, Qiaozhu Mei
|
https://iclr.cc/virtual/2021/poster/2572
|
Graph Neural Network;Gaussian Copula;Gaussian Graphical Model
| null | 0 | null | null |
iclr
| 0.57735 | 0 | null |
main
| 6.5 |
5;7;7;7
| null |
https://iclr.cc/virtual/2021/poster/2572
|
CopulaGNN: Towards Integrating Representational and Correlational Roles of Graphs in Graph Neural Networks
|
https://github.com/jiaqima/CopulaGNN
| null | 0 | 3.5 |
Poster
|
3;4;4;3
| null |
null |
Oden Institute for Computational Engineering and Sciences, University of Texas at Austin; Department of Computer Science, University of Maryland, College Park
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/3230; None
| null | 0 | null | null | null | null | null |
Phil Pope, Chen Zhu, Ahmed Abdelkader, Micah Goldblum, Tom Goldstein
|
https://iclr.cc/virtual/2021/poster/3230
|
generalization;dimension;manifold;ImageNet;CIFAR
| null | 0 | null | null |
iclr
| 0.816497 | 0 | null |
main
| 7 |
6;7;7;8
| null |
https://iclr.cc/virtual/2021/poster/3230
|
The Intrinsic Dimension of Images and Its Impact on Learning
|
https://github.com/PhillipPope/intrinsic-dimension
| null | 0 | 3.75 |
Spotlight
|
3;4;4;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Deep Learning;hyperparameter optimization;ensemble deep learning;multi-GPU
| null | 0 | null | null |
iclr
| -0.57735 | 0 | null |
main
| 3.25 |
3;3;3;4
| null | null |
Recycling sub-optimial Hyperparameter Optimization models to generate efficient Ensemble Deep Learning
| null | null | 0 | 4.5 |
Reject
|
4;5;5;4
| null |
null |
Seoul National University, Seoul, Korea
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/2972; None
| null | 0 | null | null | null | null | null |
Myeongjang Pyeon, Jihwan Moon, Taeyoung Hahn, Gunhee Kim
|
https://iclr.cc/virtual/2021/poster/2972
|
AutoML;Neural Architecture Search;Greedy Learning;Deep Learning
| null | 0 | null | null |
iclr
| 1 | 0 |
https://vision.snu.ac.kr/projects/sedona
|
main
| 6.666667 |
6;7;7
| null |
https://iclr.cc/virtual/2021/poster/2972
|
SEDONA: Search for Decoupled Neural Networks toward Greedy Block-wise Learning
| null | null | 0 | 3.666667 |
Poster
|
3;4;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
input space;random hyperplane;optimization;robustness;dimension;codimension;manifold
| null | 0 | null | null |
iclr
| -0.870388 | 0 | null |
main
| 4.75 |
4;4;5;6
| null | null |
Slice, Dice, and Optimize: Measuring the Dimension of Neural Network Class Manifolds
|
Available on Github (exact link not provided)
| null | 0 | 3.75 |
Reject
|
4;4;4;3
| null |
null |
Dept. of Electrical & Computer Engineering, University of California San Diego; Dept. of Computer Science, University of Central Florida
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/3175; None
| null | 0 | null | null | null | null | null |
Siavash Khodadadeh, Sharare Zehtabian, Saeed Vahidian, Weijia Wang, Bill Lin, Ladislau Boloni
|
https://iclr.cc/virtual/2021/poster/3175
|
Meta-learning;Unsupervised learning;GANs
| null | 0 | null | null |
iclr
| -0.333333 | 0 | null |
main
| 6.25 |
6;6;6;7
| null |
https://iclr.cc/virtual/2021/poster/3175
|
Unsupervised Meta-Learning through Latent-Space Interpolation in Generative Models
| null | null | 0 | 4.25 |
Poster
|
4;5;4;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
variational inference;uncertainty;calibration;classification
| null | 0 | null | null |
iclr
| -0.522233 | 0 | null |
main
| 4.75 |
4;4;5;6
| null | null |
Uncertainty Calibration Error: A New Metric for Multi-Class Classification
| null | null | 0 | 3.25 |
Reject
|
3;4;3;3
| null |
null |
Microsoft Research; Microsoft Dynamics 365 AI
|
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Transformer;Attention;Natural Language Processing;Language Model Pre-training;Position Encoding
| null | 0 | null | null |
iclr
| 0.174078 | 0 | null |
main
| 6.25 |
6;6;6;7
| null | null |
DEBERTA: DECODING-ENHANCED BERT WITH DISENTANGLED ATTENTION
|
https://github.com/microsoft/DeBERTa1
| null | 0 | 3.75 |
Poster
|
5;3;3;4
| null |
null |
Facebook AI Research; University of Toronto; Vector Institute
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/2747; None
| null | 0 | null | null | null | null | null |
Tian Qi Chen, Brandon Amos, Maximilian Nickel
|
https://iclr.cc/virtual/2021/poster/2747
|
point processes;normalizing flows;differential equations
| null | 0 | null | null |
iclr
| 0.174078 | 0 | null |
main
| 6.25 |
5;6;7;7
| null |
https://iclr.cc/virtual/2021/poster/2747
|
Neural Spatio-Temporal Point Processes
| null | null | 0 | 3.75 |
Poster
|
4;3;4;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
orthogonal polynomials;differentiation;compression;nonconvex optimization
| null | 0 | null | null |
iclr
| 0.5 | 0 | null |
main
| 4.666667 |
4;4;6
| null | null |
Optimizing Over All Sequences of Orthogonal Polynomials
| null | null | 0 | 3.666667 |
Withdraw
|
3;4;4
| null |
null |
University of Cambridge, The Alan Turing Institute; University of Cambridge; University of Cambridge, University of Liverpool
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/2741; None
| null | 0 | null | null | null | null | null |
Javier Antorán, Umang Bhatt, Tameem Adel, Adrian Weller, José Miguel Hernández Lobato
|
https://iclr.cc/virtual/2021/poster/2741
|
interpretability;uncertainty;explainability
| null | 0 | null | null |
iclr
| -0.57735 | 0 | null |
main
| 6.75 |
6;7;7;7
| null |
https://iclr.cc/virtual/2021/poster/2741
|
Getting a CLUE: A Method for Explaining Uncertainty Estimates
| null | null | 0 | 3.5 |
Oral
|
4;3;3;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Meta learning;NAS;Fast adaptation
| null | 0 | null | null |
iclr
| -0.870388 | 0 | null |
main
| 4.25 |
3;4;5;5
| null | null |
Connection-Adaptive Meta-Learning
| null | null | 0 | 4.25 |
Withdraw
|
5;4;4;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null | null | null | 0 | null | null |
iclr
| 0 | 0 | null |
main
| 4.25 |
4;4;4;5
| null | null |
Mirror Sample Based Distribution Alignment for Unsupervised Domain Adaption
| null | null | 0 | 5 |
Withdraw
|
5;5;5;5
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Knowledge Distillation;Deep Learning;Supervised Learning;Model Compression
| null | 0 | null | null |
iclr
| -0.408248 | 0 | null |
main
| 5 |
3;5;6;6
| null | null |
Can Students Outperform Teachers in Knowledge Distillation based Model Compression?
| null | null | 0 | 4.5 |
Reject
|
5;4;4;5
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
Gaussian Process;Gaussian Process Regression
| null | 0 | null | null |
iclr
| -0.777778 | 0 | null |
main
| 4.25 |
3;3;5;6
| null | null |
Learning What Not to Model: Gaussian Process Regression with Negative Constraints
| null | null | 0 | 3.5 |
Reject
|
4;4;4;2
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null |
unsupervised representation learning;robustness;transfer learning
| null | 0 | null | null |
iclr
| 0.5 | 0 | null |
main
| 6.333333 |
5;7;7
| null | null |
Transferable Unsupervised Robust Representation Learning
| null | null | 0 | 4.333333 |
Reject
|
4;5;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null | null | null | 0 | null | null |
iclr
| -0.333333 | 0 | null |
main
| 4.5 |
3;5;5;5
| null | null |
GN-Transformer: Fusing AST and Source Code information in Graph Networks
| null | null | 0 | 3.75 |
Reject
|
4;4;3;4
| null |
null |
Department of Computer Science & Technology, Institute for AI, BNRist Center, Tsinghua-Bosch Joint ML Center, THBI Lab, Tsinghua University, Beijing, 100084 China
|
2021
| 0 |
https://iclr.cc/virtual/2021/poster/2754; None
| null | 0 | null | null | null | null | null |
Tianyu Pang, Xiao Yang, Yinpeng Dong, Hang Su, Jun Zhu
|
https://iclr.cc/virtual/2021/poster/2754
|
Adversarial Training;Robustness;Adversarial Examples
| null | 0 | null | null |
iclr
| 0.426401 | 0 | null |
main
| 6.25 |
5;6;7;7
| null |
https://iclr.cc/virtual/2021/poster/2754
|
Bag of Tricks for Adversarial Training
|
https://github.com/P2333/Bag-of-Tricks-for-AT
| null | 0 | 4 |
Poster
|
3;5;4;4
| null |
null | null |
2021
| 0 | null | null | 0 | null | null | null | null | null | null | null | null | null | 0 | null | null |
iclr
| -0.301511 | 0 | null |
main
| 3.75 |
3;3;4;5
| null | null |
Empirically Verifying Hypotheses Using Reinforcement Learning
| null | null | 0 | 3.5 |
Reject
|
4;3;4;3
| null |
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