Bachman, Philip

21 publications

NeurIPS 2023 Ignorance Is Bliss: Robust Control via Information Gating Manan Tomar, Riashat Islam, Matthew Taylor, Sergey Levine, Philip Bachman

ICMLW 2023 Video-Guided Skill Discovery Manan Tomar, Dibya Ghosh, Vivek Myers, Anca Dragan, Matthew E. Taylor, Philip Bachman, Sergey Levine

ICLR 2021 Data-Efficient Reinforcement Learning with Self-Predictive Representations Max Schwarzer, Ankesh Anand, Rishab Goel, R Devon Hjelm, Aaron Courville, Philip Bachman

ICML 2021 Decomposed Mutual Information Estimation for Contrastive Representation Learning Alessandro Sordoni, Nouha Dziri, Hannes Schulz, Geoff Gordon, Philip Bachman, Remi Tachet Des Combes

NeurIPS 2021 Pretraining Representations for Data-Efficient Reinforcement Learning Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, R Devon Hjelm, Philip Bachman, Aaron C. Courville

NeurIPS 2020 Deep Reinforcement and InfoMax Learning Bogdan Mazoure, Remi Tachet des Combes, Thang Long Doan, Philip Bachman, R Devon Hjelm

NeurIPS 2019 Learning Representations by Maximizing Mutual Information Across Views Philip Bachman, R Devon Hjelm, William Buchwalter

ICML 2018 Augmented CycleGAN: Learning Many-to-Many Mappings from Unpaired Data Amjad Almahairi, Sai Rajeshwar, Alessandro Sordoni, Philip Bachman, Aaron Courville

AAAI 2018 Deep Reinforcement Learning That Matters Peter Henderson, Riashat Islam, Philip Bachman, Joelle Pineau, Doina Precup, David Meger

ICLR 2017 Calibrating Energy-Based Generative Adversarial Networks Zihang Dai, Amjad Almahairi, Philip Bachman, Eduard H. Hovy, Aaron C. Courville

ICML 2017 Learning Algorithms for Active Learning Philip Bachman, Alessandro Sordoni, Adam Trischler

ICLR 2017 Learning Algorithms for Active Learning Philip Bachman, Alessandro Sordoni, Adam Trischler

ICLR 2017 Natural Language Generation in Dialogue Using Lexicalized and Delexicalized Data Shikhar Sharma, Jing He, Kaheer Suleman, Hannes Schulz, Philip Bachman

NeurIPS 2016 An Architecture for Deep, Hierarchical Generative Models Philip Bachman

NeurIPS 2015 Data Generation as Sequential Decision Making Philip Bachman, Doina Precup

ICML 2015 Variational Generative Stochastic Networks with Collaborative Shaping Philip Bachman, Doina Precup

NeurIPS 2014 Learning with Pseudo-Ensembles Philip Bachman, Ouais Alsharif, Doina Precup

ICML 2014 Sample-Based Approximate Regularization Philip Bachman, Amir-Massoud Farahmand, Doina Precup

ECML-PKDD 2013 Greedy Confidence Pursuit: A Pragmatic Approach to Multi-Bandit Optimization Philip Bachman, Doina Precup

ICML 2012 Improved Estimation in Time Varying Models Doina Precup, Philip Bachman

AAAI 2011 Learning Compact Representations of Time-Varying Processes Philip Bachman, Doina Precup