Anirudh Goyal

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 126

Top Venues

CoRR

ICLR

ICML

NeurIPS

Publications

Siyuan Guo, Aniket Didolkar, Nan Rosemary Ke, Anirudh Goyal, Ferenc Huszár, Bernhard Schölkopf
Learning Beyond Pattern Matching? Assaying Mathematical Understanding in LLMs. CoRR (2024)
Haonan Wang, James Zou, Michael Mozer, Anirudh Goyal, Alex Lamb, Linjun Zhang, Weijie J. Su, Zhun Deng, Michael Qizhe Xie, Hannah Brown, Kenji Kawaguchi
Can AI Be as Creative as Humans? CoRR (2024)
Vedant Shah, Dingli Yu, Kaifeng Lyu, Simon Park, Nan Rosemary Ke, Michael Mozer, Yoshua Bengio, Sanjeev Arora, Anirudh Goyal
AI-Assisted Generation of Difficult Math Questions. CoRR (2024)
Cristian Meo, Louis Mahon, Anirudh Goyal, Justin Dauwels
αTC-VAE: On the relationship between Disentanglement and Diversity. ICLR (2024)
Yiran Zhao, Wenyue Zheng, Tianle Cai, Xuan Long Do, Kenji Kawaguchi, Anirudh Goyal, Michael Shieh
Accelerating Greedy Coordinate Gradient via Probe Sampling. CoRR (2024)
Yuxi Xie, Anirudh Goyal, Wenyue Zheng, Min-Yen Kan, Timothy P. Lillicrap, Kenji Kawaguchi, Michael Shieh
Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning. CoRR (2024)
Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Siyuan Guo, Michal Valko, Timothy P. Lillicrap, Danilo J. Rezende, Yoshua Bengio, Michael Mozer, Sanjeev Arora
Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving. CoRR (2024)
Ayush Agrawal, Raghav Prabhakar, Anirudh Goyal, Dianbo Liu
Physical Reasoning and Object Planning for Household Embodied Agents. Trans. Mach. Learn. Res. 2024 (2024)
Cristian Meo, Ksenia Sycheva, Anirudh Goyal, Justin Dauwels
Bayesian-LoRA: LoRA based Parameter Efficient Fine-Tuning using Optimal Quantization levels and Rank Values trough Differentiable Bayesian Gates. CoRR (2024)
Dingli Yu, Simran Kaur, Arushi Gupta, Jonah Brown-Cohen, Anirudh Goyal, Sanjeev Arora
SKILL-MIX: a Flexible and Expandable Family of Evaluations for AI Models. ICLR (2024)
Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, Anirudh Goyal, Anthony Hartshorn, Aobo Yang, Archi Mitra, Archie Sravankumar, Artem Korenev, Arthur Hinsvark, Arun Rao, Aston Zhang, Aurélien Rodriguez, Austen Gregerson, Ava Spataru, Baptiste Rozière, Bethany Biron, Binh Tang, Bobbie Chern, Charlotte Caucheteux, Chaya Nayak, Chloe Bi, Chris Marra, Chris McConnell, Christian Keller, Christophe Touret, Chunyang Wu, Corinne Wong, Cristian Canton Ferrer, Cyrus Nikolaidis, Damien Allonsius, Daniel Song, Danielle Pintz, Danny Livshits, David Esiobu, Dhruv Choudhary, Dhruv Mahajan, Diego Garcia-Olano, Diego Perino, Dieuwke Hupkes, Egor Lakomkin, Ehab AlBadawy, Elina Lobanova, Emily Dinan, Eric Michael Smith, Filip Radenovic, Frank Zhang, Gabriel Synnaeve, Gabrielle Lee, Georgia Lewis Anderson, Graeme Nail, Grégoire Mialon, Guan Pang, Guillem Cucurell, Hailey Nguyen, Hannah Korevaar, Hu Xu, Hugo Touvron, Iliyan Zarov, Imanol Arrieta Ibarra, Isabel M. Kloumann, Ishan Misra, Ivan Evtimov, Jade Copet, Jaewon Lee, Jan Geffert, Jana Vranes, Jason Park, Jay Mahadeokar, Jeet Shah, Jelmer van der Linde, Jennifer Billock, Jenny Hong, Jenya Lee, Jeremy Fu, Jianfeng Chi, Jianyu Huang, Jiawen Liu, Jie Wang, Jiecao Yu, Joanna Bitton, Joe Spisak, Jongsoo Park, Joseph Rocca, Joshua Johnstun, Joshua Saxe, Junteng Jia, Kalyan Vasuden Alwala, Kartikeya Upasani, Kate Plawiak, Ke Li, Kenneth Heafield, Kevin Stone, et al.
The Llama 3 Herd of Models. CoRR (2024)
Aniket Rajiv Didolkar, Anirudh Goyal, Yoshua Bengio
Cycle Consistency Driven Object Discovery. ICLR (2024)
Kaifeng Lyu, Haoyu Zhao, Xinran Gu, Dingli Yu, Anirudh Goyal, Sanjeev Arora
Keeping LLMs Aligned After Fine-tuning: The Crucial Role of Prompt Templates. CoRR (2024)
Riashat Islam, Hongyu Zang, Manan Tomar, Aniket Didolkar, Md Mofijul Islam, Samin Yeasar Arnob, Tariq Iqbal, Xin Li, Anirudh Goyal, Nicolas Heess, Alex Lamb
Representation Learning in Deep RL via Discrete Information Bottleneck. AISTATS (2023)
Sumukh K. Aithal, Anirudh Goyal, Alex Lamb, Yoshua Bengio, Michael Mozer
Leveraging the Third Dimension in Contrastive Learning. CoRR (2023)
Ayush Agrawal, Raghav Prabhakar, Anirudh Goyal, Dianbo Liu
Physical Reasoning and Object Planning for Household Embodied Agents. CoRR (2023)
Cristian Meo, Anirudh Goyal, Justin Dauwels
TC-VAE: Uncovering Out-of-Distribution Data Generative Factors. CoRR (2023)
Vedant Shah, Frederik Träuble, Ashish Malik, Hugo Larochelle, Michael Mozer, Sanjeev Arora, Yoshua Bengio, Anirudh Goyal
Unlearning via Sparse Representations. CoRR (2023)
Dianbo Liu, Moksh Jain, Bonaventure F. P. Dossou, Qianli Shen, Salem Lahlou, Anirudh Goyal, Nikolay Malkin, Chris Chinenye Emezue, Dinghuai Zhang, Nadhir Hassen, Xu Ji, Kenji Kawaguchi, Yoshua Bengio
GFlowOut: Dropout with Generative Flow Networks. ICML (2023)
Mihir Prabhudesai, Anirudh Goyal, Deepak Pathak, Katerina Fragkiadaki
Aligning Text-to-Image Diffusion Models with Reward Backpropagation. CoRR (2023)
Dingli Yu, Simran Kaur, Arushi Gupta, Jonah Brown-Cohen, Anirudh Goyal, Sanjeev Arora
Skill-Mix: a Flexible and Expandable Family of Evaluations for AI models. CoRR (2023)
Nan Rosemary Ke, Silvia Chiappa, Jane X. Wang, Jörg Bornschein, Anirudh Goyal, Mélanie Rey, Theophane Weber, Matthew M. Botvinick, Michael Curtis Mozer, Danilo Jimenez Rezende
Learning to Induce Causal Structure. ICLR (2023)
Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Bernhard Schölkopf, Michael Curtis Mozer, Christopher Pal, Yoshua Bengio
Neural Causal Structure Discovery from Interventions. Trans. Mach. Learn. Res. 2023 (2023)
Mihir Prabhudesai, Anirudh Goyal, Sujoy Paul, Sjoerd van Steenkiste, Mehdi S. M. Sajjadi, Gaurav Aggarwal, Thomas Kipf, Deepak Pathak, Katerina Fragkiadaki
Test-time Adaptation with Slot-Centric Models. ICML (2023)
Dianbo Liu, Vedant Shah, Oussama Boussif, Cristian Meo, Anirudh Goyal, Tianmin Shu, Michael Curtis Mozer, Nicolas Heess, Yoshua Bengio
Stateful Active Facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning. ICLR (2023)
Frederik Träuble, Anirudh Goyal, Nasim Rahaman, Michael Curtis Mozer, Kenji Kawaguchi, Yoshua Bengio, Bernhard Schölkopf
Discrete Key-Value Bottleneck. ICML (2023)
Sanjeev Arora, Anirudh Goyal
A Theory for Emergence of Complex Skills in Language Models. CoRR (2023)
Nan Rosemary Ke, Sara-Jane Dunn, Jörg Bornschein, Silvia Chiappa, Mélanie Rey, Jean-Baptiste Lespiau, Albin Cassirer, Jane X. Wang, Theophane Weber, David G. T. Barrett, Matthew M. Botvinick, Anirudh Goyal, Michael Mozer, Danilo J. Rezende
DiscoGen: Learning to Discover Gene Regulatory Networks. CoRR (2023)
Aniket Didolkar, Anirudh Goyal, Yoshua Bengio
Cycle Consistency Driven Object Discovery. CoRR (2023)
Ayush Chakravarthy, Trang Nguyen, Anirudh Goyal, Yoshua Bengio, Michael C. Mozer
Spotlight Attention: Robust Object-Centric Learning With a Spatial Locality Prior. CoRR (2023)
Anirudh Goyal, Abram L. Friesen, Andrea Banino, Theophane Weber, Nan Rosemary Ke, Adrià Puigdomènech Badia, Arthur Guez, Mehdi Mirza, Peter C. Humphreys, Ksenia Konyushkova, Michal Valko, Simon Osindero, Timothy P. Lillicrap, Nicolas Heess, Charles Blundell
Retrieval-Augmented Reinforcement Learning. ICML (2022)
Nino Scherrer, Anirudh Goyal, Stefan Bauer, Yoshua Bengio, Nan Rosemary Ke
On the Generalization and Adaption Performance of Causal Models. CoRR (2022)
Samarth Sinha, Karsten Roth, Anirudh Goyal, Marzyeh Ghassemi, Zeynep Akata, Hugo Larochelle, Animesh Garg
Uniform Priors for Data-Efficient Learning. CVPR Workshops (2022)
Dianbo Liu, Vedant Shah, Oussama Boussif, Cristian Meo, Anirudh Goyal, Tianmin Shu, Michael Mozer, Nicolas Heess, Yoshua Bengio
Stateful active facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning. CoRR (2022)
Aniket Didolkar, Kshitij Gupta, Anirudh Goyal, Nitesh B. Gundavarapu, Alex Lamb, Nan Rosemary Ke, Yoshua Bengio
Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning. NeurIPS (2022)
Riashat Islam, Hongyu Zang, Manan Tomar, Aniket Didolkar, Md Mofijul Islam, Samin Yeasar Arnob, Tariq Iqbal, Xin Li, Anirudh Goyal, Nicolas Heess, Alex Lamb
Representation Learning in Deep RL via Discrete Information Bottleneck. CoRR (2022)
Anirudh Goyal, Abram L. Friesen, Andrea Banino, Theophane Weber, Nan Rosemary Ke, Adrià Puigdomènech Badia, Arthur Guez, Mehdi Mirza, Ksenia Konyushkova, Michal Valko, Simon Osindero, Timothy P. Lillicrap, Nicolas Heess, Charles Blundell
Retrieval-Augmented Reinforcement Learning. CoRR (2022)
Mihir Prabhudesai, Anirudh Goyal, Deepak Pathak, Katerina Fragkiadaki
Generating Fast and Slow: Scene Decomposition via Reconstruction. CoRR (2022)
Riashat Islam, Hongyu Zang, Anirudh Goyal, Alex M. Lamb, Kenji Kawaguchi, Xin Li, Romain Laroche, Yoshua Bengio, Remi Tachet des Combes
Discrete Compositional Representations as an Abstraction for Goal Conditioned Reinforcement Learning. NeurIPS (2022)
Nan Rosemary Ke, Silvia Chiappa, Jane Wang, Jörg Bornschein, Theophane Weber, Anirudh Goyal, Matthew M. Botvinick, Michael Mozer, Danilo Jimenez Rezende
Learning to Induce Causal Structure. CoRR (2022)
Anirudh Goyal, Aniket Rajiv Didolkar, Alex Lamb, Kartikeya Badola, Nan Rosemary Ke, Nasim Rahaman, Jonathan Binas, Charles Blundell, Michael Curtis Mozer, Yoshua Bengio
Coordination Among Neural Modules Through a Shared Global Workspace. ICLR (2022)
Aniket Didolkar, Kshitij Gupta, Anirudh Goyal, Alex Lamb, Nan Rosemary Ke, Yoshua Bengio
Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning. CoRR (2022)
Frederik Träuble, Anirudh Goyal, Nasim Rahaman, Michael Mozer, Kenji Kawaguchi, Yoshua Bengio, Bernhard Schölkopf
Discrete Key-Value Bottleneck. CoRR (2022)
Dianbo Liu, Moksh Jain, Bonaventure Dossou, Qianli Shen, Salem Lahlou, Anirudh Goyal, Nikolay Malkin, Chris Emezue, Dinghuai Zhang, Nadhir Hassen, Xu Ji, Kenji Kawaguchi, Yoshua Bengio
GFlowOut: Dropout with Generative Flow Networks. CoRR (2022)
David Silver, Anirudh Goyal, Ivo Danihelka, Matteo Hessel, Hado van Hasselt
Learning by Directional Gradient Descent. ICLR (2022)
Riashat Islam, Hongyu Zang, Anirudh Goyal, Alex Lamb, Kenji Kawaguchi, Xin Li, Romain Laroche, Yoshua Bengio, Remi Tachet des Combes
Discrete Factorial Representations as an Abstraction for Goal Conditioned Reinforcement Learning. CoRR (2022)
Dianbo Liu, Vedant Shah, Oussama Boussif, Cristian Meo, Anirudh Goyal, Tianmin Shu, Michael Mozer, Nicolas Heess, Yoshua Bengio
Coordinating Policies Among Multiple Agents via an Intelligent Communication Channel. CoRR (2022)
Kanika Madan, Nan Rosemary Ke, Anirudh Goyal, Bernhard Schölkopf, Yoshua Bengio
Fast And Slow Learning Of Recurrent Independent Mechanisms. ICLR (2021)
Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Charles Blundell, Sergey Levine, Yoshua Bengio, Michael Curtis Mozer
Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments. ICLR (2021)
Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Charles Blundell, Philippe Beaudoin, Nicolas Heess, Michael Mozer, Yoshua Bengio
Neural Production Systems. NeurIPS (2021)
Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal, Anirudh Goyal, Guillaume Lajoie, Stefan Bauer, Danilo Jimenez Rezende, Michael Mozer, Yoshua Bengio, Chris Pal
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning. NeurIPS Datasets and Benchmarks (2021)
Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael Curtis Mozer, Yoshua Bengio
Discrete-Valued Neural Communication. CoRR (2021)
Kanika Madan, Nan Rosemary Ke, Anirudh Goyal, Bernhard Schölkopf, Yoshua Bengio
Fast and Slow Learning of Recurrent Independent Mechanisms. CoRR (2021)
Yashas Annadani, Jonas Rothfuss, Alexandre Lacoste, Nino Scherrer, Anirudh Goyal, Yoshua Bengio, Stefan Bauer
Variational Causal Networks: Approximate Bayesian Inference over Causal Structures. CoRR (2021)
Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal, Anirudh Goyal, Guillaume Lajoie, Stefan Bauer, Danilo J. Rezende, Yoshua Bengio, Michael Mozer, Christopher J. Pal
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning. CoRR (2021)
Stefan Bauer, Manuel Wüthrich, Felix Widmaier, Annika Buchholz, Sebastian Stark, Anirudh Goyal, Thomas Steinbrenner, Joel Akpo, Shruti Joshi, Vincent Berenz, Vaibhav Agrawal, Niklas Funk, Julen Urain De Jesus, Jan Peters, Joe Watson, Claire Chen, Krishnan Srinivasan, Junwu Zhang, Jeffrey Zhang, Matthew R. Walter, Rishabh Madan, Takuma Yoneda, Denis Yarats, Arthur Allshire, Ethan K. Gordon, Tapomayukh Bhattacharjee, Siddhartha S. Srinivasa, Animesh Garg, Takahiro Maeda, Harshit Sikchi, Jilong Wang, Qingfeng Yao, Shuyu Yang, Robert McCarthy, Francisco Sanchez, Qiang Wang, David Cordova Bulens, Kevin McGuinness, Noel E. O'Connor, Stephen J. Redmond, Bernhard Schölkopf
Real Robot Challenge: A Robotics Competition in the Cloud. NeurIPS (Competition and Demos) (2021)
Alex Lamb, Di He, Anirudh Goyal, Guolin Ke, Chien-Feng Liao, Mirco Ravanelli, Yoshua Bengio
Transformers with Competitive Ensembles of Independent Mechanisms. CoRR (2021)
Bernhard Schölkopf, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke, Nal Kalchbrenner, Anirudh Goyal, Yoshua Bengio
Towards Causal Representation Learning. CoRR (2021)
Anirudh Goyal, Aniket Didolkar, Nan Rosemary Ke, Charles Blundell, Philippe Beaudoin, Nicolas Heess, Michael Mozer, Yoshua Bengio
Neural Production Systems. CoRR (2021)
Anirudh Goyal, Aniket Didolkar, Alex Lamb, Kartikeya Badola, Nan Rosemary Ke, Nasim Rahaman, Jonathan Binas, Charles Blundell, Michael Mozer, Yoshua Bengio
Coordination Among Neural Modules Through a Shared Global Workspace. CoRR (2021)
Samarth Sinha, Homanga Bharadhwaj, Anirudh Goyal, Hugo Larochelle, Animesh Garg, Florian Shkurti
DIBS: Diversity Inducing Information Bottleneck in Model Ensembles. AAAI (2021)
Alex Lamb, Anirudh Goyal, Agnieszka Slowik, Michael Mozer, Philippe Beaudoin, Yoshua Bengio
Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers. AISTATS (2021)
Saeid Asgari Taghanaki, Kristy Choi, Amir Hosein Khasahmadi, Anirudh Goyal
Robust Representation Learning via Perceptual Similarity Metrics. ICML (2021)
Frederik Träuble, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, Stefan Bauer
On Disentangled Representations Learned from Correlated Data. ICML (2021)
Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael C. Mozer, Yoshua Bengio
Discrete-Valued Neural Communication. NeurIPS (2021)
Saeid Asgari Taghanaki, Kristy Choi, Amir Khasahmadi, Anirudh Goyal
Robust Representation Learning via Perceptual Similarity Metrics. CoRR (2021)
Bernhard Schölkopf, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke, Nal Kalchbrenner, Anirudh Goyal, Yoshua Bengio
Toward Causal Representation Learning. Proc. IEEE 109 (5) (2021)
Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schölkopf
Recurrent Independent Mechanisms. ICLR (2021)
Ossama Ahmed, Frederik Träuble, Anirudh Goyal, Alexander Neitz, Manuel Wuthrich, Yoshua Bengio, Bernhard Schölkopf, Stefan Bauer
CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning. ICLR (2021)
Nasim Rahaman, Anirudh Goyal, Muhammad Waleed Gondal, Manuel Wuthrich, Stefan Bauer, Yash Sharma, Yoshua Bengio, Bernhard Schölkopf
Spatially Structured Recurrent Modules. ICLR (2021)
Nino Scherrer, Olexa Bilaniuk, Yashas Annadani, Anirudh Goyal, Patrick Schwab, Bernhard Schölkopf, Michael C. Mozer, Yoshua Bengio, Stefan Bauer, Nan Rosemary Ke
Learning Neural Causal Models with Active Interventions. CoRR (2021)
Anirudh Goyal, Yoshua Bengio
Inductive Biases for Deep Learning of Higher-Level Cognition. CoRR (2020)
Nasim Rahaman, Steffen Wolf, Anirudh Goyal, Roman Remme, Yoshua Bengio
Learning the Arrow of Time for Problems in Reinforcement Learning. ICLR (2020)
Samarth Sinha, Anirudh Goyal, Colin Raffel, Augustus Odena
Top-K Training of GANs: Improving Generators by Making Critics Less Critical. CoRR (2020)
Samarth Sinha, Homanga Bharadhwaj, Anirudh Goyal, Hugo Larochelle, Animesh Garg, Florian Shkurti
DIBS: Diversity inducing Information Bottleneck in Model Ensembles. CoRR (2020)
Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules. ICML (2020)
Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Sergey Levine, Charles Blundell, Yoshua Bengio, Michael Mozer
Object Files and Schemata: Factorizing Declarative and Procedural Knowledge in Dynamical Systems. CoRR (2020)
Giancarlo Kerg, Bhargav Kanuparthi, Anirudh Goyal, Kyle Goyette, Yoshua Bengio, Guillaume Lajoie
Untangling tradeoffs between recurrence and self-attention in neural networks. CoRR (2020)
Ossama Ahmed, Frederik Träuble, Anirudh Goyal, Alexander Neitz, Manuel Wüthrich, Yoshua Bengio, Bernhard Schölkopf, Stefan Bauer
CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning. CoRR (2020)
Anirudh Goyal, Shagun Sodhani, Jonathan Binas, Xue Bin Peng, Sergey Levine, Yoshua Bengio
Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives. ICLR (2020)
Anirudh Goyal, Yoshua Bengio, Matthew Botvinick, Sergey Levine
The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget. CoRR (2020)
Frederik Träuble, Elliot Creager, Niki Kilbertus, Anirudh Goyal, Francesco Locatello, Bernhard Schölkopf, Stefan Bauer
Is Independence all you need? On the Generalization of Representations Learned from Correlated Data. CoRR (2020)
Nasim Rahaman, Anirudh Goyal, Muhammad Waleed Gondal, Manuel Wuthrich, Stefan Bauer, Yash Sharma, Yoshua Bengio, Bernhard Schölkopf
S2RMs: Spatially Structured Recurrent Modules. CoRR (2020)
Samarth Sinha, Anirudh Goyal, Animesh Garg
Maximum Entropy Models for Fast Adaptation. CoRR (2020)
Dhaval Adjodah, Dan Calacci, Abhimanyu Dubey, Anirudh Goyal, P. M. Krafft, Esteban Moro, Alex Pentland
Leveraging Communication Topologies Between Learning Agents in Deep Reinforcement Learning. AAMAS (2020)
Yoshua Bengio, Tristan Deleu, Nasim Rahaman, Nan Rosemary Ke, Sébastien Lachapelle, Olexa Bilaniuk, Anirudh Goyal, Christopher J. Pal
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms. ICLR (2020)
Anirudh Goyal, Yoshua Bengio, Matthew Botvinick, Sergey Levine
The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget. ICLR (2020)
Alex Lamb, Anirudh Goyal, Agnieszka Slowik, Michael Mozer, Philippe Beaudoin, Yoshua Bengio
Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers. CoRR (2020)
Samarth Sinha, Zhengli Zhao, Anirudh Goyal, Colin Raffel, Augustus Odena
Top-k Training of GANs: Improving GAN Performance by Throwing Away Bad Samples. NeurIPS (2020)
Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules. CoRR (2020)
Samarth Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena
Small-GAN: Speeding up GAN Training using Core-Sets. ICML (2020)
Giancarlo Kerg, Bhargav Kanuparthi, Anirudh Goyal, Kyle Goyette, Yoshua Bengio, Guillaume Lajoie
Untangling tradeoffs between recurrence and self-attention in artificial neural networks. NeurIPS (2020)
Samarth Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena
Small-GAN: Speeding Up GAN Training Using Core-sets. CoRR (2019)
Alex Lamb, Jonathan Binas, Anirudh Goyal, Sandeep Subramanian, Ioannis Mitliagkas, Denis Kazakov, Yoshua Bengio, Michael C. Mozer
State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations. CoRR (2019)
Nan Rosemary Ke, Amanpreet Singh, Ahmed Touati, Anirudh Goyal, Yoshua Bengio, Devi Parikh, Dhruv Batra
Modeling the Long Term Future in Model-Based Reinforcement Learning. ICLR (Poster) (2019)
Alex Lamb, Jonathan Binas, Anirudh Goyal, Sandeep Subramanian, Ioannis Mitliagkas, Yoshua Bengio, Michael Mozer
State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations. ICML (2019)
Yoshua Bengio, Tristan Deleu, Nasim Rahaman, Nan Rosemary Ke, Sébastien Lachapelle, Olexa Bilaniuk, Anirudh Goyal, Christopher J. Pal
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms. CoRR (2019)
Nasim Rahaman, Steffen Wolf, Anirudh Goyal, Roman Remme, Yoshua Bengio
Learning the Arrow of Time. CoRR (2019)
Shagun Sodhani, Anirudh Goyal, Tristan Deleu, Yoshua Bengio, Sergey Levine, Jian Tang
Learning Powerful Policies by Using Consistent Dynamics Model. CoRR (2019)
Rithesh Kumar, Anirudh Goyal, Aaron C. Courville, Yoshua Bengio
Maximum Entropy Generators for Energy-Based Models. CoRR (2019)

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Publication Activity (10 Years)

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Anirudh Goyal