ICLR

Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning

Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, Luke Vilnis, Ishan Durugkar, Akshay Krishnamurthy, Alex Smola, Andrew McCallum

Comments ICLR 2018

Towards Metamerism via Foveated Style Transfer

Arturo Deza, Aditya Jonnalagadda, Miguel Eckstein

Comments Published at ICLR 2019

Hierarchical Generative Modeling for Controllable Speech Synthesis

Wei-Ning Hsu, Yu Zhang, Ron J. Weiss, Heiga Zen, Yonghui Wu, Yuxuan Wang, Yuan Cao, Ye Jia, Zhifeng Chen, Jonathan Shen, Patrick Nguyen, Ruoming Pang

Comments 27 pages, accepted to ICLR 2019

Variational Inference of Disentangled Latent Concepts from Unlabeled Observations

Abhishek Kumar, Prasanna Sattigeri, Avinash Balakrishnan

Comments ICLR 2018 Version

Learning when to Communicate at Scale in Multiagent Cooperative and Competitive Tasks

Amanpreet Singh, Tushar Jain, Sainbayar Sukhbaatar

Comments Accepted to ICLR 2019

NADPEx: An on-policy temporally consistent exploration method for deep reinforcement learning

Sirui Xie, Junning Huang, Lanxin Lei, Chunxiao Liu, Zheng Ma, Wei Zhang, Liang Lin

Comments To appear in ICLR 2019

On the loss landscape of a class of deep neural networks with no bad local valleys

Quynh Nguyen, Mahesh Chandra Mukkamala, Matthias Hein

Comments Accepted at ICLR 2019

Preconditioner on Matrix Lie Group for SGD

Xi-Lin Li

Comments to appear on ICLR 2019

Reward Constrained Policy Optimization

Chen Tessler, Daniel J. Mankowitz, Shie Mannor

Comments Accepted as a poster to ICLR 2019

Unsupervised Speech Recognition via Segmental Empirical Output Distribution Matching

Chih-Kuan Yeh, Jianshu Chen, Chengzhu Yu, Dong Yu

Comments Published as a conference paper at ICLR 2019

Learning to Navigate the Web

Izzeddin Gur, Ulrich Rueckert, Aleksandra Faust, Dilek Hakkani-Tur

Comments International Conference on Learning Representations (ICLR), 2019

Slimmable Neural Networks

Jiahui Yu, Linjie Yang, Ning Xu, Jianchao Yang, Thomas Huang

Comments Accepted in ICLR 2019

Fluctuation-dissipation relations for stochastic gradient descent

Sho Yaida

Comments 15 pages, 6 figures; v2: final version accepted at ICLR 2019, with derivations/assumptions clarified and Adam/AMSGrad experiments added

Deep Graph Infomax

Petar Veličković, William Fedus, William L. Hamilton, Pietro Liò, Yoshua Bengio, R Devon Hjelm

Comments To appear at ICLR 2019. 17 pages, 8 figures

Reproduction Report on "Learn to Pay Attention"

Levan Shugliashvili, Davit Soselia, Shota Amashukeli, Irakli Koberidze

Comments 2 pages, 2 tables, originally made for the ICLR 2018 Reproducibility Challenge

Feature Learning in Deep Neural Networks - Studies on Speech Recognition Tasks

Dong Yu, Michael L. Seltzer, Jinyu Li, Jui-Ting Huang, Frank Seide

Comments ICLR 2013, 9 pages, 4 figures

Learning Finite State Representations of Recurrent Policy Networks

Anurag Koul, Sam Greydanus, Alan Fern

Comments Preprint. Under review at ICLR 2019

Diffusion Scattering Transforms on Graphs

Fernando Gama, Alejandro Ribeiro, Joan Bruna

Comments Submitted to the International Conference on Learning Representations (ICLR 2019)

A Differentiable Physics Engine for Deep Learning in Robotics

Jonas Degrave, Michiel Hermans, Joni Dambre, Francis wyffels

Comments Submitted for International Conference on Learning Representations 2017

Activation Maximization Generative Adversarial Nets

Zhiming Zhou, Han Cai, Shu Rong, Yuxuan Song, Kan Ren, Weinan Zhang, Yong Yu, Jun Wang

Comments Accepted as a conference paper on ICLR 2018

Deep Ensemble Bayesian Active Learning : Addressing the Mode Collapse issue in Monte Carlo dropout via Ensembles

Remus Pop, Patric Fulop

Comments ICLR under review

Generative Models of Visually Grounded Imagination

Ramakrishna Vedantam, Ian Fischer, Jonathan Huang, Kevin Murphy

Comments International Conference on Learning Representations (ICLR), 2018

Reward Estimation for Variance Reduction in Deep Reinforcement Learning

Joshua Romoff, Peter Henderson, Alexandre Piché, Vincent Francois-Lavet, Joelle Pineau

Comments Version 1 as appears in the International Conference on Learning Representations (ICLR) 2018 Workshop Track; Version 2 as appears in the Proceedings of The 2nd Conference on Robot Learning

Learning a Generative Model for Validity in Complex Discrete Structures

David Janz, Jos van der Westhuizen, Brooks Paige, Matt J. Kusner, José Miguel Hernández-Lobato

Comments Conference paper at ICLR 2018. Code available online

Reproducing AmbientGAN: Generative models from lossy measurements

Mehdi Ahmadi, Timothy Nest, Mostafa Abdelnaim, Thanh-Dung Le

Comments This work was submitted as final project for the course IFT6135: Representation Learning - A Deep Learning Course, University of Montreal, Winter 2018

Journal ref ICLR 2018 Reproducibility Challenge

Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension

Rajarshi Das, Tsendsuren Munkhdalai, Xingdi Yuan, Adam Trischler, Andrew McCallum

Comments ICLR 2019 submission

Interpreting Adversarial Robustness: A View from Decision Surface in Input Space

Fuxun Yu, Chenchen Liu, Yanzhi Wang, Liang Zhao, Xiang Chen

Comments 15 pages, submitted to ICLR 2019

Divide and Conquer Networks

Alex Nowak-Vila, David Folqué, Joan Bruna

Comments ICLR 2018

Optimized Gated Deep Learning Architectures for Sensor Fusion

Myung Seok Shim, Peng Li

Comments 10 pages, 5 figures. Submitted to ICLR 2019

Local Explanation Methods for Deep Neural Networks Lack Sensitivity to Parameter Values

Julius Adebayo, Justin Gilmer, Ian Goodfellow, Been Kim

Comments Workshop Track International Conference on Learning Representations (ICLR)