ICLR

Weakly Supervised Clustering by Exploiting Unique Class Count

Mustafa Umit Oner, Hwee Kuan Lee, Wing-Kin Sung

Comments Published as a conference paper at ICLR 2020

CM3: Cooperative Multi-goal Multi-stage Multi-agent Reinforcement Learning

Jiachen Yang, Alireza Nakhaei, David Isele, Kikuo Fujimura, Hongyuan Zha

Comments Published at International Conference on Learning Representations 2020

Kernel of CycleGAN as a Principle homogeneous space

Nikita Moriakov, Jonas Adler, Jonas Teuwen

Comments Accepted at ICLR 2020

Graph Constrained Reinforcement Learning for Natural Language Action Spaces

Prithviraj Ammanabrolu, Matthew Hausknecht

Comments Accepted to ICLR 2020

Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation

Byung Hoon Ahn, Prannoy Pilligundla, Amir Yazdanbakhsh, Hadi Esmaeilzadeh

Comments Published as a conference paper at ICLR 2020. arXiv admin note: text overlap with arXiv:1905.12799

Target-Embedding Autoencoders for Supervised Representation Learning

Daniel Jarrett, Mihaela van der Schaar

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

How Much Position Information Do Convolutional Neural Networks Encode?

Md Amirul Islam, Sen Jia, Neil D. B. Bruce

Comments Accepted to ICLR 2020

IMPACT: Importance Weighted Asynchronous Architectures with Clipped Target Networks

Michael Luo, Jiahao Yao, Richard Liaw, Eric Liang, Ion Stoica

Comments ICLR 2020 Publication; 14 pages, 10 figures

Intensity-Free Learning of Temporal Point Processes

Oleksandr Shchur, Marin Biloš, Stephan Günnemann

Comments International Conference on Learning Representations (ICLR) 2020

Mixout: Effective Regularization to Finetune Large-scale Pretrained Language Models

Cheolhyoung Lee, Kyunghyun Cho, Wanmo Kang

Comments Published as a conference paper at ICLR 2020

On Mutual Information Maximization for Representation Learning

Michael Tschannen, Josip Djolonga, Paul K. Rubenstein, Sylvain Gelly, Mario Lucic

Comments ICLR 2020. Michael Tschannen and Josip Djolonga contributed equally

BlockSwap: Fisher-guided Block Substitution for Network Compression on a Budget

Jack Turner, Elliot J. Crowley, Michael O'Boyle, Amos Storkey, Gavin Gray

Comments ICLR 2020

Automated curricula through setter-solver interactions

Sebastien Racaniere, Andrew K. Lampinen, Adam Santoro, David P. Reichert, Vlad Firoiu, Timothy P. Lillicrap

Journal ref International Conference on Learning Representations, 2020

Learning to Control PDEs with Differentiable Physics

Philipp Holl, Vladlen Koltun, Nils Thuerey

Comments Published as a conference paper at ICLR 2020. Main text: 10 pages, 6 figures, 3 tables. Total: 28 pages, 18 figures

Smooth markets: A basic mechanism for organizing gradient-based learners

David Balduzzi, Wojciech M Czarnecki, Thomas W Anthony, Ian M Gemp, Edward Hughes, Joel Z Leibo, Georgios Piliouras, Thore Graepel

Comments 18 pages, 3 figures

Journal ref ICLR 2020

Composition-based Multi-Relational Graph Convolutional Networks

Shikhar Vashishth, Soumya Sanyal, Vikram Nitin, Partha Talukdar

Comments In Proceedings of ICLR 2020

DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures

Huanrui Yang, Wei Wen, Hai Li

Comments To be appeared in ICLR 2020 (poster presentation)

InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization

Fan-Yun Sun, Jordan Hoffmann, Vikas Verma, Jian Tang

Comments ICLR 2020 (spotlight)

SNODE: Spectral Discretization of Neural ODEs for System Identification

Alessio Quaglino, Marco Gallieri, Jonathan Masci, Jan Koutník

Comments Published as a conference paper at ICLR 2020

Graph Inference Learning for Semi-supervised Classification

Chunyan Xu, Zhen Cui, Xiaobin Hong, Tong Zhang, Jian Yang, Wei Liu

Comments 11 pages

Journal ref International Conference on Learning Representations (ICLR), 2020

FasterSeg: Searching for Faster Real-time Semantic Segmentation

Wuyang Chen, Xinyu Gong, Xianming Liu, Qian Zhang, Yuan Li, Zhangyang Wang

Comments ICLR 2020 accepted

Provable Benefit of Orthogonal Initialization in Optimizing Deep Linear Networks

Wei Hu, Lechao Xiao, Jeffrey Pennington

Comments International Conference on Learning Representations (ICLR) 2020

Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space

AkshatKumar Nigam, Pascal Friederich, Mario Krenn, Alán Aspuru-Guzik

Comments 9+3 Pages, 7+4 figures, 2 tables. Comments are welcome! (code is available at: https://github.com/aspuru-guzik-group/GA)

Journal ref International Conference on Learning Representations (ICLR-2020)

Spectral Inference Networks: Unifying Deep and Spectral Learning

David Pfau, Stig Petersen, Ashish Agarwal, David G. T. Barrett, Kimberly L. Stachenfeld

Comments Fixed typo in math in section 4

Journal ref Seventh International Conference on Learning Representations (ICLR 2019)

Unsupervised Learning of the Set of Local Maxima

Lior Wolf, Sagie Benaim, Tomer Galanti

Comments ICLR 2019

Emerging Disentanglement in Auto-Encoder Based Unsupervised Image Content Transfer

Ori Press, Tomer Galanti, Sagie Benaim, Lior Wolf

Journal ref ICLR 2019

Neural Arithmetic Units

Andreas Madsen, Alexander Rosenberg Johansen

Comments International Conference on Learning Representations, 2020

A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning

Soochan Lee, Junsoo Ha, Dongsu Zhang, Gunhee Kim

Comments Accepted as a conference paper at ICLR 2020

NAS-Bench-201: Extending the Scope of Reproducible Neural Architecture Search

Xuanyi Dong, Yi Yang

Comments Published at ICLR 2020 as a spotlight paper; 16 pages; 10 figures; 7 tables; Code is available at https://github.com/D-X-Y/AutoDL-Projects

Neural Execution of Graph Algorithms

Petar Veličković, Rex Ying, Matilde Padovano, Raia Hadsell, Charles Blundell

Comments To appear at ICLR 2020. 13 pages, 4 figures