ICLR

LowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial Recognition

Valeriia Cherepanova, Micah Goldblum, Harrison Foley, Shiyuan Duan, John Dickerson, Gavin Taylor, Tom Goldstein

Comments Published as a conference paper at ICLR 2021

Contrastive Learning with Hard Negative Samples

Joshua Robinson, Ching-Yao Chuang, Suvrit Sra, Stefanie Jegelka

Comments Published as a conference paper at ICLR 2021

Grounding Language to Autonomously-Acquired Skills via Goal Generation

Ahmed Akakzia, Cédric Colas, Pierre-Yves Oudeyer, Mohamed Chetouani, Olivier Sigaud

Comments Published at ICLR 2021

Learning Task-General Representations with Generative Neuro-Symbolic Modeling

Reuben Feinman, Brenden M. Lake

Journal ref International Conference on Learning Representations (ICLR 2021)

Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes

Jake Snell, Richard Zemel

Comments Extended version of accepted ICLR 2021 submission. 34 pages, 9 figures

LEAF: A Learnable Frontend for Audio Classification

Neil Zeghidour, Olivier Teboul, Félix de Chaumont Quitry, Marco Tagliasacchi

Comments Accepted at ICLR 2021

Robust Reinforcement Learning on State Observations with Learned Optimal Adversary

Huan Zhang, Hongge Chen, Duane Boning, Cho-Jui Hsieh

Comments Accepted by ICLR 2021. Huan Zhang and Hongge Chen contributed equally

Categorical Normalizing Flows via Continuous Transformations

Phillip Lippe, Efstratios Gavves

Comments Submitted to: International Conference on Learning Representations (ICLR), 2021

Semi-supervised Keypoint Localization

Olga Moskvyak, Frederic Maire, Feras Dayoub, Mahsa Baktashmotlagh

Comments accepted to ICLR 2021

Few-Shot Bayesian Optimization with Deep Kernel Surrogates

Martin Wistuba, Josif Grabocka

Comments Published as a conference paper at ICLR 2021

Interpretable Models for Granger Causality Using Self-explaining Neural Networks

Ričards Marcinkevičs, Julia E. Vogt

Comments ICLR 2021

The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods

Louis Thiry, Michael Arbel, Eugene Belilovsky, Edouard Oyallon

Journal ref International Conference on Learning Representation (ICLR 2021), 2021, Vienna (online), Austria

Disentangled Recurrent Wasserstein Autoencoder

Jun Han, Martin Renqiang Min, Ligong Han, Li Erran Li, Xuan Zhang

Comments ICLR 2021

What makes instance discrimination good for transfer learning?

Nanxuan Zhao, Zhirong Wu, Rynson W. H. Lau, Stephen Lin

Comments Accepted by ICLR 2021

Lossless Compression of Structured Convolutional Models via Lifting

Gustav Sourek, Filip Zelezny, Ondrej Kuzelka

Comments Accepted to ICLR 2021. TL;DR: Speeding up weight-sharing dynamic neural computation graphs, such as GNNs, with lifted inference

Differentiable Segmentation of Sequences

Erik Scharwächter, Jonathan Lennartz, Emmanuel Müller

Comments source codes available at https://github.com/diozaka/diffseg

Journal ref International Conference on Learning Representations (ICLR) 2021

AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights

Byeongho Heo, Sanghyuk Chun, Seong Joon Oh, Dongyoon Han, Sangdoo Yun, Gyuwan Kim, Youngjung Uh, Jung-Woo Ha

Comments Accepted at ICLR 2021. First two authors contributed equally

On Data-Augmentation and Consistency-Based Semi-Supervised Learning

Atin Ghosh, Alexandre H. Thiery

Journal ref ICLR 2021

Contrastive Explanations for Reinforcement Learning via Embedded Self Predictions

Zhengxian Lin, Kim-Ho Lam, Alan Fern

Comments Published (Oral) at ICLR 2021

Adversarial Policies: Attacking Deep Reinforcement Learning

Adam Gleave, Michael Dennis, Cody Wild, Neel Kant, Sergey Levine, Stuart Russell

Comments Presented at ICLR 2020

Density Modeling of Images using a Generalized Normalization Transformation

Johannes Ballé, Valero Laparra, Eero P. Simoncelli

Comments published as a conference paper at ICLR 2016

Journal ref Int'l Conf on Learning Representations (ICLR), San Juan, Puerto Rico, May 2016

Local Search Algorithms for Rank-Constrained Convex Optimization

Kyriakos Axiotis, Maxim Sviridenko

Comments Accepted in ICLR 2021

Heating up decision boundaries: isocapacitory saturation, adversarial scenarios and generalization bounds

Bogdan Georgiev, Lukas Franken, Mayukh Mukherjee

Comments Accepted as conference paper at ICLR 2021. 36 pages, 16 figures, comments welcome!

Counterfactual Generative Networks

Axel Sauer, Andreas Geiger

Comments Published at ICLR 2021

Physics-aware, probabilistic model order reduction with guaranteed stability

Sebastian Kaltenbach, Phaedon-Stelios Koutsourelakis

Comments ICLR 2021

A Diffusion Theory For Deep Learning Dynamics: Stochastic Gradient Descent Exponentially Favors Flat Minima

Zeke Xie, Issei Sato, Masashi Sugiyama

Comments ICLR 2021; 28 pages; 19 figures

DICE: Diversity in Deep Ensembles via Conditional Redundancy Adversarial Estimation

Alexandre Rame, Matthieu Cord

Comments Published as a conference paper at ICLR 2021. 9 main pages, 13 figures, 12 tables

Support-set bottlenecks for video-text representation learning

Mandela Patrick, Po-Yao Huang, Yuki Asano, Florian Metze, Alexander Hauptmann, João Henriques, Andrea Vedaldi

Comments Accepted as spotlight paper at the International Conference on Learning Representations (ICLR) 2021

Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy

Danica J. Sutherland, Hsiao-Yu Tung, Heiko Strathmann, Soumyajit De, Aaditya Ramdas, Alex Smola, Arthur Gretton

Comments Published at ICLR 2017 (public comments: http://openreview.net/forum?id=HJWHIKqgl )

Demystifying MMD GANs

Mikołaj Bińkowski, Danica J. Sutherland, Michael Arbel, Arthur Gretton

Comments Published at ICLR 2018: https://openreview.net/forum?id=r1lUOzWCW