Anirudh Goyal

Towards Causal Representation Learning

Feb 22, 2021
Bernhard Schölkopf, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke, Nal Kalchbrenner, Anirudh Goyal, Yoshua Bengio

* Special Issue of Proceedings of the IEEE - Advances in Machine Learning and Deep Neural Networks

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Inductive Biases for Deep Learning of Higher-Level Cognition

Dec 07, 2020
Anirudh Goyal, Yoshua Bengio

* This document contains a review of authors research as part of the requirement of AG's predoctoral exam, an overview of the main contributions of the authors few recent papers (co-authored with several other co-authors) as well as a vision of proposed future research

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Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers

Oct 15, 2020
Alex Lamb, Anirudh Goyal, Agnieszka Słowik, Michael Mozer, Philippe Beaudoin, Yoshua Bengio

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CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning

Oct 08, 2020
Ossama Ahmed, Frederik Träuble, Anirudh Goyal, Alexander Neitz, Manuel Wüthrich, Yoshua Bengio, Bernhard Schölkopf, Stefan Bauer

* The first two authors contributed equally

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S2RMs: Spatially Structured Recurrent Modules

Jul 13, 2020
Nasim Rahaman, Anirudh Goyal, Muhammad Waleed Gondal, Manuel Wuthrich, Stefan Bauer, Yash Sharma, Yoshua Bengio, Bernhard Schölkopf

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Object Files and Schemata: Factorizing Declarative and Procedural Knowledge in Dynamical Systems

Jun 30, 2020
Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Sergey Levine, Charles Blundell, Yoshua Bengio, Michael Mozer

* Under Review, NeurIPS 2020

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Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules

Jun 30, 2020
Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio

* ICML 2020

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Maximum Entropy Models for Fast Adaptation

Jun 30, 2020
Samarth Sinha, Anirudh Goyal, Animesh Garg

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Untangling tradeoffs between recurrence and self-attention in neural networks

Jun 16, 2020
Giancarlo Kerg, Bhargav Kanuparthi, Anirudh Goyal, Kyle Goyette, Yoshua Bengio, Guillaume Lajoie

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Is Independence all you need? On the Generalization of Representations Learned from Correlated Data

Jun 14, 2020
Frederik Träuble, Elliot Creager, Niki Kilbertus, Anirudh Goyal, Francesco Locatello, Bernhard Schölkopf, Stefan Bauer

* 33 pages, 33 figures

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The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget

Apr 24, 2020
Anirudh Goyal, Yoshua Bengio, Matthew Botvinick, Sergey Levine

* Published as a conference paper at ICLR 2020

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DIBS: Diversity inducing Information Bottleneck in Model Ensembles

Mar 10, 2020
Samarth Sinha, Homanga Bharadhwaj, Anirudh Goyal, Hugo Larochelle, Animesh Garg, Florian Shkurti

* Samarth Sinha* and Homanga Bharadhwaj* contributed equally to this work. Code will be released at https://github.com/rvl-lab-utoronto/dibs

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