ICLR

Towards causal generative scene models via competition of experts

Julius von Kügelgen, Ivan Ustyuzhaninov, Peter Gehler, Matthias Bethge, Bernhard Schölkopf

Comments Presented at the ICLR 2020 workshop "Causal learning for decision making"

Empirical Bayes Transductive Meta-Learning with Synthetic Gradients

Shell Xu Hu, Pablo G. Moreno, Yang Xiao, Xi Shen, Guillaume Obozinski, Neil D. Lawrence, Andreas Damianou

Comments ICLR 2020

The Ingredients of Real-World Robotic Reinforcement Learning

Henry Zhu, Justin Yu, Abhishek Gupta, Dhruv Shah, Kristian Hartikainen, Avi Singh, Vikash Kumar, Sergey Levine

Comments First three authors contributed equally. Accepted as a spotlight presentation at ICLR 2020

Transferable Perturbations of Deep Feature Distributions

Nathan Inkawhich, Kevin J Liang, Lawrence Carin, Yiran Chen

Comments Published as a conference paper at ICLR 2020

Learning to Guide Random Search

Ozan Sener, Vladlen Koltun

Comments Published at ICLR 2020, Code is available at: https://github.com/intel-isl/LMRS

Thinking While Moving: Deep Reinforcement Learning with Concurrent Control

Ted Xiao, Eric Jang, Dmitry Kalashnikov, Sergey Levine, Julian Ibarz, Karol Hausman, Alexander Herzog

Comments Published as a conference paper at ICLR 2020

Regularizing activations in neural networks via distribution matching with the Wasserstein metric

Taejong Joo, Donggu Kang, Byunghoon Kim

Comments ICLR 2020

Symplectic Recurrent Neural Networks

Zhengdao Chen, Jianyu Zhang, Martin Arjovsky, Léon Bottou

Comments Added link to GitHub repository

Journal ref 8th International Conference on Learning Representations (ICLR 2020)

WHAI: Weibull Hybrid Autoencoding Inference for Deep Topic Modeling

Hao Zhang, Bo Chen, Dandan Guo, Mingyuan Zhou

Comments ICLR 2018

Ensemble Adversarial Training: Attacks and Defenses

Florian Tramèr, Alexey Kurakin, Nicolas Papernot, Ian Goodfellow, Dan Boneh, Patrick McDaniel

Comments 22 pages, 5 figures, International Conference on Learning Representations (ICLR) 2018 (amended in April 2020 to include subsequent attacks that significantly reduced the robustness of our models)

The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget

Anirudh Goyal, Yoshua Bengio, Matthew Botvinick, Sergey Levine

Comments Published as a conference paper at ICLR 2020

SMArtCast: Predicting soil moisture interpolations into the future using Earth observation data in a deep learning framework

Conrad James Foley, Sagar Vaze, Mohamed El Amine Seddiq, Alexey Unagaev, Natalia Efremova

Comments Climate change AI workshop

Journal ref ICLR 2020

Lite Transformer with Long-Short Range Attention

Zhanghao Wu, Zhijian Liu, Ji Lin, Yujun Lin, Song Han

Comments ICLR 2020. The first two authors contributed equally to this work

Residual Energy-Based Models for Text Generation

Yuntian Deng, Anton Bakhtin, Myle Ott, Arthur Szlam, Marc'Aurelio Ranzato

Comments published at ICLR 2020. arXiv admin note: substantial text overlap with arXiv:2004.10188

Journal ref ICLR 2020

Satellite-based Prediction of Forage Conditions for Livestock in Northern Kenya

Andrew Hobbs, Stacey Svetlichnaya

Comments Paper presented at the ICLR 2020 Workshop on Computer Vision for Agriculture (CV4A)

Hyper-spectral NIR and MIR data and optimal wavebands for detection of apple tree diseases

Dmitrii Shadrin, Mariia Pukalchik, Anastasia Uryasheva, Evgeny Tsykunov, Grigoriy Yashin, Nikita Rodichenko, Dzmitry Tsetserukou

Comments Paper presented at the ICLR 2020 Workshop on Computer Vision for Agriculture (CV4A)

Multi-agent Reinforcement Learning for Networked System Control

Tianshu Chu, Sandeep Chinchali, Sachin Katti

Comments ICLR 2020

Learning to solve the credit assignment problem

Benjamin James Lansdell, Prashanth Ravi Prakash, Konrad Paul Kording

Comments 18 pages; 4 figures. (ICLR 2020 version)

EMPIR: Ensembles of Mixed Precision Deep Networks for Increased Robustness against Adversarial Attacks

Sanchari Sen, Balaraman Ravindran, Anand Raghunathan

Comments Published as a conference paper at ICLR 2020

TrueBranch: Metric Learning-based Verification of Forest Conservation Projects

Simona Santamaria, David Dao, Björn Lütjens, Ce Zhang

Comments *Authors have contributed equally. Published as Spotlight Presentation at ICLR 2020 Workshop on Tackling Climate Change with Machine Learning

Combining Pretrained High-Resource Embeddings and Subword Representations for Low-Resource Languages

Machel Reid, Edison Marrese-Taylor, Yutaka Matsuo

Comments Accepted to the "AfricaNLP - Unlocking Local Languages" workshop at ICLR 2020

Time Adaptive Reinforcement Learning

Chris Reinke

Comments ICLR 2020 Workshop: Beyond Tabula Rasa in Reinforcement Learning

Train, Learn, Expand, Repeat

Abhijeet Parida, Aadhithya Sankar, Rami Eisawy, Tom Finck, Benedikt Wiestler, Franz Pfister, Julia Moosbauer

Comments Published as a workshop paper at AI4AH, ICLR 2020

SALSA-TEXT : self attentive latent space based adversarial text generation

Jules Gagnon-Marchand, Hamed Sadeghi, Md. Akmal Haidar, Mehdi Rezagholizadeh

Comments 10 pages, 3 figures, under review at ICLR 2019

Journal ref Canadian AI 2019

Goal-conditioned Batch Reinforcement Learning for Rotation Invariant Locomotion

Aditi Mavalankar

Comments Accepted to the BeTR-RL workshop at ICLR 2020. Link to code: https://github.com/aditimavalankar/gc-batch-rl-locomotion

Deep Sets for Generalization in RL

Tristan Karch, Cédric Colas, Laetitia Teodorescu, Clément Moulin-Frier, Pierre-Yves Oudeyer

Comments 15 pages, 10 figures, published as a workshop Paper at ICLR: Beyond tabula rasa in RL (BeTR-RL). arXiv admin note: substantial text overlap with arXiv:2002.09253

Meta Reinforcement Learning with Autonomous Inference of Subtask Dependencies

Sungryull Sohn, Hyunjae Woo, Jongwook Choi, Honglak Lee

Comments Published in ICLR 2020

From Inference to Generation: End-to-end Fully Self-supervised Generation of Human Face from Speech

Hyeong-Seok Choi, Changdae Park, Kyogu Lee

Comments 18 pages, 12 figures, Published as a conference paper at International Conference on Learning Representations (ICLR) 2020. (camera-ready version)

Minimizing FLOPs to Learn Efficient Sparse Representations

Biswajit Paria, Chih-Kuan Yeh, Ian E. H. Yen, Ning Xu, Pradeep Ravikumar, Barnabás Póczos

Comments Published at ICLR 2020

Gradients as Features for Deep Representation Learning

Fangzhou Mu, Yingyu Liang, Yin Li

Comments ICLR 2020 conference paper