Anirudh Goyal
anirudhgoyal9119 at gmail dot com

I am a graduate student in CS at University of Montreal. I am a part of Mila, advised by Prof. Yoshua Bengio.

Before graduate school, I received a Bachelors in Computer Science at IIIT Hyderabad, where I worked on several research projects at CVIT under Prof. C.V Jawahar. I have also spent time at Google.

Google Scholar  /  GitHub

News
Invited Talks and Lectures
Mentoring
Current
Sarthak Mittal
Aniket Didolkar
Phanideep Gampa

Past
Soumye Singhal
Samarth Sinha

Publications

Preprints

Is Independence all you need? On the Generalization of Representations Learned from Correlated Data
Frederik Träuble , Elliot Creager , Niki Kilbertus , Anirudh Goyal, Francesco Locatello , Bernhard Schölkopf, Stefan Bauer
arXiv

Recurrent Independent Mechanisms
Anirudh Goyal, Alex Lamb, Jordan Hoffmann , Shagun Sodhani , Sergey Levine, Bernhard Schölkopf, Yoshua Bengio
arXiv / code

Learning Neural Causal Models from unknown Interventions
Nan Rosemary Ke , Olexa Bilaniuk , Anirudh Goyal, Stefan Bauer , Bernhard Schölkopf, Michael C. Mozer, Hugo Larochelle, Chris Pal , Yoshua Bengio
arXiv / code

Top-K Training of GANs: Improving Generators by Making Critics Less Critical
Samarth Sinha , Anirudh Goyal, Colin Raffel , Augustus Odena
arXiv

Maximum Entropy Generators for Energy-Based Models
Rithesh Kumar , Sherjil Ozair , Anirudh Goyal, Aaron Courville , Yoshua Bengio
arXiv / code

DIBS: Diversity inducing Information Bottleneck in Model Ensembles
Samarth Sinha , Homanga Bharadhwaj , Anirudh Goyal, Hugo Larochelle, Animesh Garg , Florian Shkurti
arXiv

2020

Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules
Sarthak Mittal , Alex Lamb, Anirudh Goyal, Murray Shanahan , Guillaume Lajoie , Michael C. Mozer, Yoshua Bengio
International Conference on Machine Learning (ICML), 2020
arXiv (coming soon!)

Small-GAN: Speeding Up GAN Training Using Core-sets
Samarth Sinha , Han Zhang , Anirudh Goyal, Yoshua Bengio , Hugo Larochelle, Augustus Odena
International Conference on Machine Learning (ICML), 2020
arXiv

Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives
Anirudh Goyal, Shagun Sodhani, Jonathan Binas , Xue Bin (Jason) Peng , Sergey Levine, Yoshua Bengio
International Conference on Learning Representations (ICLR), 2020
arXiv

The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget
Anirudh Goyal, Yoshua Bengio , Matthew Botvinick , Sergey Levine
International Conference on Learning Representations (ICLR), 2020
arXiv

A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms
Yoshua Bengio , Tristan Deleu , Nasim Rahaman , Nan Rosemary Ke , Sebastien Lachapelle , Olexa Bilaniuk , Anirudh Goyal, Chris Pal
International Conference on Learning Representations (ICLR), 2020
arXiv / code

Learning the Arrow of Time for Problems in Reinforcement Learning
Nasim Rahaman , Steffen Wolf , Anirudh Goyal, Roman Remme , Yoshua Bengio
International Conference on Learning Representations (ICLR), 2020
arXiv / code

2019

State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations
Alex Lamb, Jonathan Binas , Anirudh Goyal, Sandeep Subramanian , Yoshua Bengio , Michael C. Mozer
International Conference on Machine Learning (ICML), 2019
arXiv / code

Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future
Nan Rosemary Ke , Amanpreet Singh , Ahmed Touati , Anirudh Goyal, Yoshua Bengio , Devi Parikh , Dhruv Batra
International Conference on Learning Representations (ICLR), 2019
arXiv / code

InfoBot: Transfer and Exploration via the Information Bottleneck
Anirudh Goyal, Riashat Islam , Daniel Strouse , Zafarali Ahmed , Matthew Botvinick , Hugo Larochelle, Sergey Levine, Yoshua Bengio
International Conference on Learning Representations (ICLR), 2019
arXiv

Recall Traces: Backtracking Models for Efficient Reinforcement Learning
Anirudh Goyal, Philemon Brakel , William Fedus , Soumye Singhal , Timothy Lillicrap , Hugo Larochelle, Sergey Levine, Yoshua Bengio
International Conference on Learning Representations (ICLR), 2019
arXiv / code

2018

Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding
Nan Rosemary Ke , Anirudh Goyal, Olexa Bilaniuk , Jonathan Binas , Michael C. Mozer, Chris Pal, Yoshua Bengio
Advances in Neural Information Processing Systems (NIPS) , 2018
arXiv / code

Generalization of Equilibrium Propagation to Vector Field Dynamics
Benjamin Scellier , Anirudh Goyal, Jonathan Binas , Yoshua Bengio
International Conference on Learning Representations Workshop (ICLR), 2018
arXiv

2017

Z-Forcing: Training Stochastic Recurrent Networks
Anirudh Goyal, Alessandro Sordoni , Marc-Alexandre Côté , Nan Rosemary Ke , Yoshua Bengio
Advances in Neural Information Processing Systems (NIPS) , 2017
arXiv / code

Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net
Anirudh Goyal, Nan Rosemary Ke , Surya Ganguli , Yoshua Bengio
Advances in Neural Information Processing Systems (NIPS) , 2017
arXiv / code

Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations
David Krueger , Tegan Maharaj , János Kramár , Mohammad Pezeshki , Nicolas Ballas , Nan Rosemary Ke , Anirudh Goyal, Yoshua Bengio , Aaron Courville , Chris Pal
International Conference on Learning Representations (ICLR), 2017
arXiv / code

An Actor-Critic Algorithm for Sequence Prediction
Dzmitry Bahdanau , Philemon Brakel , Kelvin Xu , Anirudh Goyal, Ryan Lowe , Joelle Pineau , Aaron Courville , Yoshua Bengio
International Conference on Learning Representations (ICLR), 2017
arXiv / code

2016

Professor Forcing: A New Algorithm for Training Recurrent Networks
Anirudh Goyal, Alex Lamb , Ying Zhang , Saizheng Zhang , Aaron Courville , Yoshua Bengio
Advances in Neural Information Processing Systems (NIPS) , 2016
arXiv / code