Anirudh Goyal - RankMe

161 papers A* 44A 3Journal 100Unranked 14

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Alien Science: Sampling Coherent but Cognitively Unavailable Research Directions from Idea Atoms. CoRR Alejandro H. Artiles, Martin Weiss, Levin Brinkmann, Anirudh Goyal, Nasim Rahaman
2026	J	`jnl`	Escaping the Cognitive Well: Efficient Competition Math with Off-the-Shelf Models. CoRR Xingyu Dang, Rohit Agarwal, Rodrigo Porto, Anirudh Goyal, Liam H. Fowl, Sanjeev Arora
2025	—	`conf`	A Systematic Examination of Preference Learning through the Lens of Instruction-Following. NAACL (Long Papers) Joongwon Kim, Anirudh Goyal, Aston Zhang, Bo Xiong, Rui Hou, Melanie Kambadur, Dhruv Mahajan, Hannaneh Hajishirzi, Liang Tan
2025	J	`jnl`	ASTRO: Teaching Language Models to Reason by Reflecting and Backtracking In-Context. CoRR Joongwon Kim, Anirudh Goyal, Liang Tan, Hannaneh Hajishirzi, Srinivasan Iyer, Tianlu Wang
2025	J	`jnl`	Auto-Bench: An Automated Benchmark for Scientific Discovery in LLMs. CoRR Tingting Chen, Srinivas Anumasa, Beibei Lin, Vedant Shah, Anirudh Goyal, Dianbo Liu
2025	J	`jnl`	Compute as Teacher: Turning Inference Compute Into Reference-Free Supervision. CoRR Dulhan Jayalath, Shashwat Goel, Thomas Foster, Parag Jain, Suchin Gururangan, Cheng Zhang, Anirudh Goyal, Alan Schelten
2025	A*	`conf`	Generalizing from SIMPLE to HARD Visual Reasoning: Can We Mitigate Modality Imbalance in VLMs? ICML Simon Park, Abhishek Panigrahi, Yun Cheng, Dingli Yu, Anirudh Goyal, Sanjeev Arora
2025	J	`jnl`	Generalizing from SIMPLE to HARD Visual Reasoning: Can We Mitigate Modality Imbalance in VLMs? CoRR Simon Park, Abhishek Panigrahi, Yun Cheng, Dingli Yu, Anirudh Goyal, Sanjeev Arora
2025	J	`jnl`	HypoSpace: Evaluating LLM Creativity as Set-Valued Hypothesis Generators under Underdetermination. CoRR Tingting Chen, Beibei Lin, Zifeng Yuan, Qiran Zou, Hongyu He, Yew-Soon Ong, Anirudh Goyal, Dianbo Liu
2025	A*	`conf`	Instruct-SkillMix: A Powerful Pipeline for LLM Instruction Tuning. ICLR Simran Kaur, Simon Park, Anirudh Goyal, Sanjeev Arora
2025	J	`jnl`	Low Compute Unlearning via Sparse Representations. Trans. Mach. Learn. Res. Vedant Shah, Frederik Träuble, Ashish Malik, Hugo Larochelle, Michael Curtis Mozer, Sanjeev Arora, Yoshua Bengio, Anirudh Goyal
2025	J	`jnl`	Metacognitive Reuse: Turning Recurring LLM Reasoning Into Concise Behaviors. CoRR Aniket Didolkar, Nicolas Ballas, Sanjeev Arora, Anirudh Goyal
2025	J	`jnl`	On the Impossibility of Retrain Equivalence in Machine Unlearning. CoRR Jiatong Yu, Yinghui He, Anirudh Goyal, Sanjeev Arora
2025	A*	`conf`	On the Transfer of Object-Centric Representation Learning. ICLR Aniket Rajiv Didolkar, Andrii Zadaianchuk, Anirudh Goyal, Michael Curtis Mozer, Yoshua Bengio, Georg Martius, Maximilian Seitzer
2025	J	`jnl`	Rethinking Thinking Tokens: LLMs as Improvement Operators. CoRR Lovish Madaan, Aniket Didolkar, Suchin Gururangan, John Quan, Ruan Silva, Ruslan Salakhutdinov, Manzil Zaheer, Sanjeev Arora, Anirudh Goyal
2025	A*	`conf`	SWE-Search: Enhancing Software Agents with Monte Carlo Tree Search and Iterative Refinement. ICLR Antonis Antoniades, Albert Örwall, Kexun Zhang, Yuxi Xie, Anirudh Goyal, William Yang Wang
2025	A*	`conf`	Understanding and Enhancing Safety Mechanisms of LLMs via Safety-Specific Neuron. ICLR Yiran Zhao, Wenxuan Zhang, Yuxi Xie, Anirudh Goyal, Kenji Kawaguchi, Michael Shieh
2025	A*	`conf`	Unnatural Languages Are Not Bugs but Features for LLMs. ICML Keyu Duan, Yiran Zhao, Zhili Feng, Jinjie Ni, Tianyu Pang, Qian Liu, Tianle Cai, Longxu Dou, Kenji Kawaguchi, Anirudh Goyal, J. Zico Kolter, Michael Qizhe Shieh
2025	J	`jnl`	Unnatural Languages Are Not Bugs but Features for LLMs. CoRR Keyu Duan, Yiran Zhao, Zhili Feng, Jinjie Ni, Tianyu Pang, Qian Liu, Tianle Cai, Longxu Dou, Kenji Kawaguchi, Anirudh Goyal, J. Zico Kolter, Michael Qizhe Shieh
2024	J	`jnl`	A Systematic Examination of Preference Learning through the Lens of Instruction-Following. CoRR Joongwon Kim, Anirudh Goyal, Aston Zhang, Bo Xiong, Rui Hou, Melanie Kambadur, Dhruv Mahajan, Hannaneh Hajishirzi, Liang Tan
2024	J	`jnl`	AI-Assisted Generation of Difficult Math Questions. CoRR Vedant Shah, Dingli Yu, Kaifeng Lyu, Simon Park, Nan Rosemary Ke, Michael Mozer, Yoshua Bengio, Sanjeev Arora, Anirudh Goyal
2024	A*	`conf`	Accelerating Greedy Coordinate Gradient and General Prompt Optimization via Probe Sampling. NeurIPS Yiran Zhao, Wenyue Zheng, Tianle Cai, Do Xuan Long, Kenji Kawaguchi, Anirudh Goyal, Michael Qizhe Shieh
2024	J	`jnl`	Accelerating Greedy Coordinate Gradient via Probe Sampling. CoRR Yiran Zhao, Wenyue Zheng, Tianle Cai, Xuan Long Do, Kenji Kawaguchi, Anirudh Goyal, Michael Shieh
2024	J	`jnl`	Bayesian-LoRA: LoRA based Parameter Efficient Fine-Tuning using Optimal Quantization levels and Rank Values trough Differentiable Bayesian Gates. CoRR Cristian Meo, Ksenia Sycheva, Anirudh Goyal, Justin Dauwels
2024	J	`jnl`	COrAL: Order-Agnostic Language Modeling for Efficient Iterative Refinement. CoRR Yuxi Xie, Anirudh Goyal, Xiaobao Wu, Xunjian Yin, Xiao Xu, Min-Yen Kan, Liangming Pan, William Yang Wang
2024	J	`jnl`	Can AI Be as Creative as Humans? CoRR Haonan Wang, James Zou, Michael Mozer, Anirudh Goyal, Alex Lamb, Linjun Zhang, Weijie J. Su, Zhun Deng, Michael Qizhe Xie, Hannah Brown, Kenji Kawaguchi
2024	A*	`conf`	Can Models Learn Skill Composition from Examples? NeurIPS Haoyu Zhao, Simran Kaur, Dingli Yu, Anirudh Goyal, Sanjeev Arora
2024	J	`jnl`	Can Models Learn Skill Composition from Examples? CoRR Haoyu Zhao, Simran Kaur, Dingli Yu, Anirudh Goyal, Sanjeev Arora
2024	A*	`conf`	Cycle Consistency Driven Object Discovery. ICLR Aniket Rajiv Didolkar, Anirudh Goyal, Yoshua Bengio
2024	J	`jnl`	Data for Mathematical Copilots: Better Ways of Presenting Proofs for Machine Learning. CoRR Simon Frieder, Jonas Bayer, Katherine M. Collins, Julius Berner, Jacob Loader, András Juhász, Fabian Ruehle, Sean Welleck, Gabriel Poesia, Ryan-Rhys Griffiths, Adrian Weller, Anirudh Goyal, Thomas Lukasiewicz, Timothy Gowers
2024	J	`jnl`	Instruct-SkillMix: A Powerful Pipeline for LLM Instruction Tuning. CoRR Simran Kaur, Simon Park, Anirudh Goyal, Sanjeev Arora
2024	A*	`conf`	Keeping LLMs Aligned After Fine-tuning: The Crucial Role of Prompt Templates. NeurIPS Kaifeng Lyu, Haoyu Zhao, Xinran Gu, Dingli Yu, Anirudh Goyal, Sanjeev Arora
2024	J	`jnl`	Keeping LLMs Aligned After Fine-tuning: The Crucial Role of Prompt Templates. CoRR Kaifeng Lyu, Haoyu Zhao, Xinran Gu, Dingli Yu, Anirudh Goyal, Sanjeev Arora
2024	J	`jnl`	Learning Beyond Pattern Matching? Assaying Mathematical Understanding in LLMs. CoRR Siyuan Guo, Aniket Didolkar, Nan Rosemary Ke, Anirudh Goyal, Ferenc Huszár, Bernhard Schölkopf
2024	J	`jnl`	Masked Generative Priors Improve World Models Sequence Modelling Capabilities. CoRR Cristian Meo, Mircea Lica, Zarif Ikram, Akihiro Nakano, Vedant Shah, Aniket Rajiv Didolkar, Dianbo Liu, Anirudh Goyal, Justin Dauwels
2024	A*	`conf`	Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving. NeurIPS Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Siyuan Guo, Michal Valko, Timothy P. Lillicrap, Danilo Jimenez Rezende, Yoshua Bengio, Michael C. Mozer, Sanjeev Arora
2024	J	`jnl`	Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving. CoRR Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Siyuan Guo, Michal Valko, Timothy P. Lillicrap, Danilo J. Rezende, Yoshua Bengio, Michael Mozer, Sanjeev Arora
2024	J	`jnl`	Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning. CoRR Yuxi Xie, Anirudh Goyal, Wenyue Zheng, Min-Yen Kan, Timothy P. Lillicrap, Kenji Kawaguchi, Michael Shieh
2024	J	`jnl`	Narrowing the Focus: Learned Optimizers for Pretrained Models. CoRR Gus Kristiansen, Mark Sandler, Andrey Zhmoginov, Nolan Miller, Anirudh Goyal, Jihwan Lee, Max Vladymyrov
2024	J	`jnl`	Object-Centric Temporal Consistency via Conditional Autoregressive Inductive Biases. CoRR Cristian Meo, Akihiro Nakano, Mircea Lica, Aniket Didolkar, Masahiro Suzuki, Anirudh Goyal, Mengmi Zhang, Justin Dauwels, Yutaka Matsuo, Yoshua Bengio
2024	J	`jnl`	Physical Reasoning and Object Planning for Household Embodied Agents. Trans. Mach. Learn. Res. Ayush Agrawal, Raghav Prabhakar, Anirudh Goyal, Dianbo Liu
2024	A*	`conf`	Reasoning Robustness of LLMs to Adversarial Typographical Errors. EMNLP Esther Gan, Yiran Zhao, Liying Cheng, Yancan Mao, Anirudh Goyal, Kenji Kawaguchi, Min-Yen Kan, Michael Shieh
2024	J	`jnl`	Reasoning Robustness of LLMs to Adversarial Typographical Errors. CoRR Esther Gan, Yiran Zhao, Liying Cheng, Yancan Mao, Anirudh Goyal, Kenji Kawaguchi, Min-Yen Kan, Michael Shieh
2024	A*	`conf`	SKILL-MIX: a Flexible and Expandable Family of Evaluations for AI Models. ICLR Dingli Yu, Simran Kaur, Arushi Gupta, Jonah Brown-Cohen, Anirudh Goyal, Sanjeev Arora
2024	J	`jnl`	SWE-Search: Enhancing Software Agents with Monte Carlo Tree Search and Iterative Refinement. CoRR Antonis Antoniades, Albert Örwall, Kexun Zhang, Yuxi Xie, Anirudh Goyal, William Yang Wang
2024	J	`jnl`	Zero-Shot Object-Centric Representation Learning. CoRR Aniket Didolkar, Andrii Zadaianchuk, Anirudh Goyal, Michael C. Mozer, Yoshua Bengio, Georg Martius, Maximilian Seitzer
2024	J	`jnl`	α-TCVAE: On the relationship between Disentanglement and Diversity. CoRR Cristian Meo, Louis Mahon, Anirudh Goyal, Justin Dauwels
2024	A*	`conf`	αTC-VAE: On the relationship between Disentanglement and Diversity. ICLR Cristian Meo, Louis Mahon, Anirudh Goyal, Justin Dauwels
2023	J	`jnl`	A Theory for Emergence of Complex Skills in Language Models. CoRR Sanjeev Arora, Anirudh Goyal
2023	J	`jnl`	Cycle Consistency Driven Object Discovery. CoRR Aniket Didolkar, Anirudh Goyal, Yoshua Bengio
2023	J	`jnl`	DiscoGen: Learning to Discover Gene Regulatory Networks. CoRR 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
2023	A*	`conf`	Discrete Key-Value Bottleneck. ICML Frederik Träuble, Anirudh Goyal, Nasim Rahaman, Michael Curtis Mozer, Kenji Kawaguchi, Yoshua Bengio, Bernhard Schölkopf
2023	A*	`conf`	GFlowOut: Dropout with Generative Flow Networks. ICML 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
2023	A*	`conf`	Learning to Induce Causal Structure. ICLR 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
2023	J	`jnl`	Leveraging the Third Dimension in Contrastive Learning. CoRR Sumukh K. Aithal, Anirudh Goyal, Alex Lamb, Yoshua Bengio, Michael Mozer
2023	J	`jnl`	Neural Causal Structure Discovery from Interventions. Trans. Mach. Learn. Res. Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Bernhard Schölkopf, Michael Curtis Mozer, Christopher Pal, Yoshua Bengio
2023	J	`jnl`	Physical Reasoning and Object Planning for Household Embodied Agents. CoRR Ayush Agrawal, Raghav Prabhakar, Anirudh Goyal, Dianbo Liu
2023	A	`conf`	Representation Learning in Deep RL via Discrete Information Bottleneck. AISTATS Riashat Islam, Hongyu Zang, Manan Tomar, Aniket Didolkar, Md Mofijul Islam, Samin Yeasar Arnob, Tariq Iqbal, Xin Li, Anirudh Goyal, Nicolas Heess, Alex Lamb
2023	J	`jnl`	Skill-Mix: a Flexible and Expandable Family of Evaluations for AI models. CoRR Dingli Yu, Simran Kaur, Arushi Gupta, Jonah Brown-Cohen, Anirudh Goyal, Sanjeev Arora
2023	J	`jnl`	Spotlight Attention: Robust Object-Centric Learning With a Spatial Locality Prior. CoRR Ayush Chakravarthy, Bailey Trang Nguyen, Anirudh Goyal, Yoshua Bengio, Michael C. Mozer
2023	A*	`conf`	Stateful Active Facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning. ICLR Dianbo Liu, Vedant Shah, Oussama Boussif, Cristian Meo, Anirudh Goyal, Tianmin Shu, Michael Curtis Mozer, Nicolas Heess, Yoshua Bengio
2023	A*	`conf`	Test-time Adaptation with Slot-Centric Models. ICML Mihir Prabhudesai, Anirudh Goyal, Sujoy Paul, Sjoerd van Steenkiste, Mehdi S. M. Sajjadi, Gaurav Aggarwal, Thomas Kipf, Deepak Pathak, Katerina Fragkiadaki
2023	J	`jnl`	Unlearning via Sparse Representations. CoRR Vedant Shah, Frederik Träuble, Ashish Malik, Hugo Larochelle, Michael Mozer, Sanjeev Arora, Yoshua Bengio, Anirudh Goyal
2022	J	`jnl`	Coordinating Policies Among Multiple Agents via an Intelligent Communication Channel. CoRR Dianbo Liu, Vedant Shah, Oussama Boussif, Cristian Meo, Anirudh Goyal, Tianmin Shu, Michael Mozer, Nicolas Heess, Yoshua Bengio
2022	A*	`conf`	Coordination Among Neural Modules Through a Shared Global Workspace. ICLR Anirudh Goyal, Aniket Rajiv Didolkar, Alex Lamb, Kartikeya Badola, Nan Rosemary Ke, Nasim Rahaman, Jonathan Binas, Charles Blundell, Michael Curtis Mozer, Yoshua Bengio
2022	A*	`conf`	Discrete Compositional Representations as an Abstraction for Goal Conditioned Reinforcement Learning. NeurIPS Riashat Islam, Hongyu Zang, Anirudh Goyal, Alex Lamb, Kenji Kawaguchi, Xin Li, Romain Laroche, Yoshua Bengio, Remi Tachet des Combes
2022	J	`jnl`	Discrete Factorial Representations as an Abstraction for Goal Conditioned Reinforcement Learning. CoRR Riashat Islam, Hongyu Zang, Anirudh Goyal, Alex Lamb, Kenji Kawaguchi, Xin Li, Romain Laroche, Yoshua Bengio, Remi Tachet des Combes
2022	J	`jnl`	Discrete Key-Value Bottleneck. CoRR Frederik Träuble, Anirudh Goyal, Nasim Rahaman, Michael Mozer, Kenji Kawaguchi, Yoshua Bengio, Bernhard Schölkopf
2022	J	`jnl`	GFlowOut: Dropout with Generative Flow Networks. CoRR 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
2022	J	`jnl`	Generating Fast and Slow: Scene Decomposition via Reconstruction. CoRR Mihir Prabhudesai, Anirudh Goyal, Deepak Pathak, Katerina Fragkiadaki
2022	A*	`conf`	Learning by Directional Gradient Descent. ICLR David Silver, Anirudh Goyal, Ivo Danihelka, Matteo Hessel, Hado van Hasselt
2022	J	`jnl`	Learning to Induce Causal Structure. CoRR Nan Rosemary Ke, Silvia Chiappa, Jane Wang, Jörg Bornschein, Theophane Weber, Anirudh Goyal, Matthew M. Botvinick, Michael Mozer, Danilo Jimenez Rezende
2022	J	`jnl`	On the Generalization and Adaption Performance of Causal Models. CoRR Nino Scherrer, Anirudh Goyal, Stefan Bauer, Yoshua Bengio, Nan Rosemary Ke
2022	J	`jnl`	Representation Learning in Deep RL via Discrete Information Bottleneck. CoRR Riashat Islam, Hongyu Zang, Manan Tomar, Aniket Didolkar, Md Mofijul Islam, Samin Yeasar Arnob, Tariq Iqbal, Xin Li, Anirudh Goyal, Nicolas Heess, Alex Lamb
2022	A*	`conf`	Retrieval-Augmented Reinforcement Learning. ICML Anirudh Goyal, Abram L. Friesen, Andrea Banino, Theophane Weber, Nan Rosemary Ke, Adrià Puigdomènech Badia, Arthur Guez, Mehdi Mirza, Peter Conway Humphreys, Ksenia Konyushkova, Michal Valko, Simon Osindero, Timothy P. Lillicrap, Nicolas Heess, Charles Blundell
2022	J	`jnl`	Retrieval-Augmented Reinforcement Learning. CoRR 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
2022	J	`jnl`	Stateful active facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning. CoRR Dianbo Liu, Vedant Shah, Oussama Boussif, Cristian Meo, Anirudh Goyal, Tianmin Shu, Michael Mozer, Nicolas Heess, Yoshua Bengio
2022	A*	`conf`	Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning. NeurIPS Aniket Didolkar, Kshitij Gupta, Anirudh Goyal, Nitesh B. Gundavarapu, Alex Lamb, Nan Rosemary Ke, Yoshua Bengio
2022	J	`jnl`	Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning. CoRR Aniket Didolkar, Kshitij Gupta, Anirudh Goyal, Alex Lamb, Nan Rosemary Ke, Yoshua Bengio
2022	—	`conf`	Uniform Priors for Data-Efficient Learning. CVPR Workshops Samarth Sinha, Karsten Roth, Anirudh Goyal, Marzyeh Ghassemi, Zeynep Akata, Hugo Larochelle, Animesh Garg
2021	A*	`conf`	CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning. ICLR Ossama Ahmed, Frederik Träuble, Anirudh Goyal, Alexander Neitz, Manuel Wuthrich, Yoshua Bengio, Bernhard Schölkopf, Stefan Bauer
2021	J	`jnl`	Coordination Among Neural Modules Through a Shared Global Workspace. CoRR Anirudh Goyal, Aniket Didolkar, Alex Lamb, Kartikeya Badola, Nan Rosemary Ke, Nasim Rahaman, Jonathan Binas, Charles Blundell, Michael Mozer, Yoshua Bengio
2021	A*	`conf`	DIBS: Diversity Inducing Information Bottleneck in Model Ensembles. AAAI Samarth Sinha, Homanga Bharadhwaj, Anirudh Goyal, Hugo Larochelle, Animesh Garg, Florian Shkurti
2021	A*	`conf`	Discrete-Valued Neural Communication. NeurIPS Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael C. Mozer, Yoshua Bengio
2021	J	`jnl`	Discrete-Valued Neural Communication. CoRR Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael Curtis Mozer, Yoshua Bengio
2021	A*	`conf`	Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments. ICLR Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Charles Blundell, Sergey Levine, Yoshua Bengio, Michael Curtis Mozer
2021	A*	`conf`	Fast And Slow Learning Of Recurrent Independent Mechanisms. ICLR Kanika Madan, Nan Rosemary Ke, Anirudh Goyal, Bernhard Schölkopf, Yoshua Bengio
2021	J	`jnl`	Fast and Slow Learning of Recurrent Independent Mechanisms. CoRR Kanika Madan, Nan Rosemary Ke, Anirudh Goyal, Bernhard Schölkopf, Yoshua Bengio
2021	J	`jnl`	Learning Neural Causal Models with Active Interventions. CoRR Nino Scherrer, Olexa Bilaniuk, Yashas Annadani, Anirudh Goyal, Patrick Schwab, Bernhard Schölkopf, Michael C. Mozer, Yoshua Bengio, Stefan Bauer, Nan Rosemary Ke
2021	A	`conf`	Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers. AISTATS Alex Lamb, Anirudh Goyal, Agnieszka Slowik, Michael Mozer, Philippe Beaudoin, Yoshua Bengio
2021	A*	`conf`	Neural Production Systems. NeurIPS Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Charles Blundell, Philippe Beaudoin, Nicolas Heess, Michael Mozer, Yoshua Bengio
2021	J	`jnl`	Neural Production Systems. CoRR Anirudh Goyal, Aniket Didolkar, Nan Rosemary Ke, Charles Blundell, Philippe Beaudoin, Nicolas Heess, Michael Mozer, Yoshua Bengio
2021	A*	`conf`	On Disentangled Representations Learned from Correlated Data. ICML Frederik Träuble, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, Stefan Bauer
2021	—	`conf`	Real Robot Challenge: A Robotics Competition in the Cloud. NeurIPS (Competition and Demos) 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 Roldan Sanchez, Qiang Wang, David Cordova Bulens, Kevin McGuinness, Noel E. O'Connor, Stephen J. Redmond, Bernhard Schölkopf
2021	A*	`conf`	Recurrent Independent Mechanisms. ICLR Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schölkopf
2021	A*	`conf`	Robust Representation Learning via Perceptual Similarity Metrics. ICML Saeid Asgari Taghanaki, Kristy Choi, Amir Hosein Khasahmadi, Anirudh Goyal
2021	J	`jnl`	Robust Representation Learning via Perceptual Similarity Metrics. CoRR Saeid Asgari Taghanaki, Kristy Choi, Amir Khasahmadi, Anirudh Goyal
2021	A*	`conf`	Spatially Structured Recurrent Modules. ICLR Nasim Rahaman, Anirudh Goyal, Muhammad Waleed Gondal, Manuel Wuthrich, Stefan Bauer, Yash Sharma, Yoshua Bengio, Bernhard Schölkopf
2021	—	`conf`	Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning. NeurIPS Datasets and Benchmarks Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal, Anirudh Goyal, Guillaume Lajoie, Stefan Bauer, Danilo Jimenez Rezende, Michael Mozer, Yoshua Bengio, Chris Pal
2021	J	`jnl`	Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning. CoRR Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal, Anirudh Goyal, Guillaume Lajoie, Stefan Bauer, Danilo J. Rezende, Yoshua Bengio, Michael Mozer, Christopher J. Pal
2021	J	`jnl`	Toward Causal Representation Learning. Proc. IEEE Bernhard Schölkopf, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke, Nal Kalchbrenner, Anirudh Goyal, Yoshua Bengio
2021	J	`jnl`	Towards Causal Representation Learning. CoRR Bernhard Schölkopf, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke, Nal Kalchbrenner, Anirudh Goyal, Yoshua Bengio
2021	J	`jnl`	Transformers with Competitive Ensembles of Independent Mechanisms. CoRR Alex Lamb, Di He, Anirudh Goyal, Guolin Ke, Chien-Feng Liao, Mirco Ravanelli, Yoshua Bengio
2021	J	`jnl`	Variational Causal Networks: Approximate Bayesian Inference over Causal Structures. CoRR Yashas Annadani, Jonas Rothfuss, Alexandre Lacoste, Nino Scherrer, Anirudh Goyal, Yoshua Bengio, Stefan Bauer
2020	A*	`conf`	A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms. ICLR Yoshua Bengio, Tristan Deleu, Nasim Rahaman, Nan Rosemary Ke, Sébastien Lachapelle, Olexa Bilaniuk, Anirudh Goyal, Christopher J. Pal
2020	J	`jnl`	CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning. CoRR Ossama Ahmed, Frederik Träuble, Anirudh Goyal, Alexander Neitz, Manuel Wüthrich, Yoshua Bengio, Bernhard Schölkopf, Stefan Bauer
2020	J	`jnl`	DIBS: Diversity inducing Information Bottleneck in Model Ensembles. CoRR Samarth Sinha, Homanga Bharadhwaj, Anirudh Goyal, Hugo Larochelle, Animesh Garg, Florian Shkurti
2020	J	`jnl`	Inductive Biases for Deep Learning of Higher-Level Cognition. CoRR Anirudh Goyal, Yoshua Bengio
2020	J	`jnl`	Is Independence all you need? On the Generalization of Representations Learned from Correlated Data. CoRR Frederik Träuble, Elliot Creager, Niki Kilbertus, Anirudh Goyal, Francesco Locatello, Bernhard Schölkopf, Stefan Bauer
2020	A*	`conf`	Learning the Arrow of Time for Problems in Reinforcement Learning. ICLR Nasim Rahaman, Steffen Wolf, Anirudh Goyal, Roman Remme, Yoshua Bengio
2020	A*	`conf`	Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules. ICML Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio
2020	J	`jnl`	Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules. CoRR Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio
2020	A	`conf`	Leveraging Communication Topologies Between Learning Agents in Deep Reinforcement Learning. AAMAS Dhaval Adjodah, Dan Calacci, Abhimanyu Dubey, Anirudh Goyal, P. M. Krafft, Esteban Moro, Alex Pentland
2020	J	`jnl`	Maximum Entropy Models for Fast Adaptation. CoRR Samarth Sinha, Anirudh Goyal, Animesh Garg
2020	J	`jnl`	Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers. CoRR Alex Lamb, Anirudh Goyal, Agnieszka Slowik, Michael Mozer, Philippe Beaudoin, Yoshua Bengio
2020	J	`jnl`	Object Files and Schemata: Factorizing Declarative and Procedural Knowledge in Dynamical Systems. CoRR Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Sergey Levine, Charles Blundell, Yoshua Bengio, Michael Mozer
2020	A*	`conf`	Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives. ICLR Anirudh Goyal, Shagun Sodhani, Jonathan Binas, Xue Bin Peng, Sergey Levine, Yoshua Bengio
2020	J	`jnl`	S2RMs: Spatially Structured Recurrent Modules. CoRR Nasim Rahaman, Anirudh Goyal, Muhammad Waleed Gondal, Manuel Wuthrich, Stefan Bauer, Yash Sharma, Yoshua Bengio, Bernhard Schölkopf
2020	A*	`conf`	Small-GAN: Speeding up GAN Training using Core-Sets. ICML Samarth Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena
2020	A*	`conf`	The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget. ICLR Anirudh Goyal, Yoshua Bengio, Matthew M. Botvinick, Sergey Levine
2020	J	`jnl`	The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget. CoRR Anirudh Goyal, Yoshua Bengio, Matthew M. Botvinick, Sergey Levine
2020	J	`jnl`	Top-K Training of GANs: Improving Generators by Making Critics Less Critical. CoRR Samarth Sinha, Anirudh Goyal, Colin Raffel, Augustus Odena
2020	A*	`conf`	Top-k Training of GANs: Improving GAN Performance by Throwing Away Bad Samples. NeurIPS Samarth Sinha, Zhengli Zhao, Anirudh Goyal, Colin Raffel, Augustus Odena
2020	A*	`conf`	Untangling tradeoffs between recurrence and self-attention in artificial neural networks. NeurIPS Giancarlo Kerg, Bhargav Kanuparthi, Anirudh Goyal, Kyle Goyette, Yoshua Bengio, Guillaume Lajoie
2020	J	`jnl`	Untangling tradeoffs between recurrence and self-attention in neural networks. CoRR Giancarlo Kerg, Bhargav Kanuparthi, Anirudh Goyal, Kyle Goyette, Yoshua Bengio, Guillaume Lajoie
2019	J	`jnl`	A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms. CoRR Yoshua Bengio, Tristan Deleu, Nasim Rahaman, Nan Rosemary Ke, Sébastien Lachapelle, Olexa Bilaniuk, Anirudh Goyal, Christopher J. Pal
2019	J	`jnl`	Communication Topologies Between Learning Agents in Deep Reinforcement Learning. CoRR Dhaval Adjodah, Dan Calacci, Abhimanyu Dubey, Anirudh Goyal, Peter M. Krafft, Esteban Moro, Alex Pentland
2019	—	`conf`	InfoBot: Transfer and Exploration via the Information Bottleneck. ICLR (Poster) Anirudh Goyal, Riashat Islam, Daniel Strouse, Zafarali Ahmed, Hugo Larochelle, Matthew M. Botvinick, Yoshua Bengio, Sergey Levine
2019	J	`jnl`	InfoBot: Transfer and Exploration via the Information Bottleneck. CoRR Anirudh Goyal, Riashat Islam, Daniel Strouse, Zafarali Ahmed, Matthew M. Botvinick, Hugo Larochelle, Sergey Levine, Yoshua Bengio
2019	J	`jnl`	Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future. CoRR Nan Rosemary Ke, Amanpreet Singh, Ahmed Touati, Anirudh Goyal, Yoshua Bengio, Devi Parikh, Dhruv Batra
2019	J	`jnl`	Learning Neural Causal Models from Unknown Interventions. CoRR Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Chris Pal, Yoshua Bengio
2019	J	`jnl`	Learning Powerful Policies by Using Consistent Dynamics Model. CoRR Shagun Sodhani, Anirudh Goyal, Tristan Deleu, Yoshua Bengio, Sergey Levine, Jian Tang
2019	J	`jnl`	Learning the Arrow of Time. CoRR Nasim Rahaman, Steffen Wolf, Anirudh Goyal, Roman Remme, Yoshua Bengio
2019	J	`jnl`	Maximum Entropy Generators for Energy-Based Models. CoRR Rithesh Kumar, Anirudh Goyal, Aaron C. Courville, Yoshua Bengio
2019	—	`conf`	Modeling the Long Term Future in Model-Based Reinforcement Learning. ICLR (Poster) Nan Rosemary Ke, Amanpreet Singh, Ahmed Touati, Anirudh Goyal, Yoshua Bengio, Devi Parikh, Dhruv Batra
2019	—	`conf`	Recall Traces: Backtracking Models for Efficient Reinforcement Learning. ICLR (Poster) Anirudh Goyal, Philemon Brakel, William Fedus, Soumye Singhal, Timothy P. Lillicrap, Sergey Levine, Hugo Larochelle, Yoshua Bengio
2019	J	`jnl`	Recurrent Independent Mechanisms. CoRR Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schölkopf
2019	J	`jnl`	Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives. CoRR Anirudh Goyal, Shagun Sodhani, Jonathan Binas, Xue Bin Peng, Sergey Levine, Yoshua Bengio
2019	J	`jnl`	Small-GAN: Speeding Up GAN Training Using Core-sets. CoRR Samarth Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena
2019	A*	`conf`	State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations. ICML Alex Lamb, Jonathan Binas, Anirudh Goyal, Sandeep Subramanian, Ioannis Mitliagkas, Yoshua Bengio, Michael Mozer
2019	J	`jnl`	State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations. CoRR Alex Lamb, Jonathan Binas, Anirudh Goyal, Sandeep Subramanian, Ioannis Mitliagkas, Denis Kazakov, Yoshua Bengio, Michael C. Mozer
2018	—	`conf`	Extending the Framework of Equilibrium Propagation to General Dynamics. ICLR (Workshop) Benjamin Scellier, Anirudh Goyal, Jonathan Binas, Thomas Mesnard, Yoshua Bengio
2018	J	`jnl`	Fortified Networks: Improving the Robustness of Deep Networks by Modeling the Manifold of Hidden Representations. CoRR Alex Lamb, Jonathan Binas, Anirudh Goyal, Dmitriy Serdyuk, Sandeep Subramanian, Ioannis Mitliagkas, Yoshua Bengio
2018	J	`jnl`	Generalization of Equilibrium Propagation to Vector Field Dynamics. CoRR Benjamin Scellier, Anirudh Goyal, Jonathan Binas, Thomas Mesnard, Yoshua Bengio
2018	J	`jnl`	Recall Traces: Backtracking Models for Efficient Reinforcement Learning. CoRR Anirudh Goyal, Philemon Brakel, William Fedus, Timothy P. Lillicrap, Sergey Levine, Hugo Larochelle, Yoshua Bengio
2018	A*	`conf`	Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding. NeurIPS Nan Rosemary Ke, Anirudh Goyal, Olexa Bilaniuk, Jonathan Binas, Michael C. Mozer, Chris Pal, Yoshua Bengio
2018	J	`jnl`	Sparse Attentive Backtracking: Temporal CreditAssignment Through Reminding. CoRR Nan Rosemary Ke, Anirudh Goyal, Olexa Bilaniuk, Jonathan Binas, Michael C. Mozer, Chris Pal, Yoshua Bengio
2017	J	`jnl`	ACtuAL: Actor-Critic Under Adversarial Learning. CoRR Anirudh Goyal, Nan Rosemary Ke, Alex Lamb, R. Devon Hjelm, Chris Pal, Joelle Pineau, Yoshua Bengio
2017	—	`conf`	An Actor-Critic Algorithm for Sequence Prediction. ICLR (Poster) Dzmitry Bahdanau, Philemon Brakel, Kelvin Xu, Anirudh Goyal, Ryan Lowe, Joelle Pineau, Aaron C. Courville, Yoshua Bengio
2017	J	`jnl`	Sparse Attentive Backtracking: Long-Range Credit Assignment in Recurrent Networks. CoRR Nan Rosemary Ke, Anirudh Goyal, Olexa Bilaniuk, Jonathan Binas, Laurent Charlin, Chris Pal, Yoshua Bengio
2017	—	`conf`	Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net. NIPS Anirudh Goyal, Nan Rosemary Ke, Surya Ganguli, Yoshua Bengio
2017	J	`jnl`	Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net. CoRR Anirudh Goyal, Nan Rosemary Ke, Surya Ganguli, Yoshua Bengio
2017	—	`conf`	Z-Forcing: Training Stochastic Recurrent Networks. NIPS Anirudh Goyal, Alessandro Sordoni, Marc-Alexandre Côté, Nan Rosemary Ke, Yoshua Bengio
2017	J	`jnl`	Z-Forcing: Training Stochastic Recurrent Networks. CoRR Anirudh Goyal, Alessandro Sordoni, Marc-Alexandre Côté, Nan Rosemary Ke, Yoshua Bengio
2017	—	`conf`	Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations. ICLR (Poster) David Krueger, Tegan Maharaj, János Kramár, Mohammad Pezeshki, Nicolas Ballas, Nan Rosemary Ke, Anirudh Goyal, Yoshua Bengio, Aaron C. Courville, Christopher J. Pal
2016	J	`jnl`	An Actor-Critic Algorithm for Sequence Prediction. CoRR Dzmitry Bahdanau, Philemon Brakel, Kelvin Xu, Anirudh Goyal, Ryan Lowe, Joelle Pineau, Aaron C. Courville, Yoshua Bengio
2016	—	`conf`	Professor Forcing: A New Algorithm for Training Recurrent Networks. NIPS Anirudh Goyal, Alex Lamb, Ying Zhang, Saizheng Zhang, Aaron C. Courville, Yoshua Bengio
2016	J	`jnl`	Professor Forcing: A New Algorithm for Training Recurrent Networks. CoRR Alex Lamb, Anirudh Goyal, Ying Zhang, Saizheng Zhang, Aaron C. Courville, Yoshua Bengio
2016	J	`jnl`	Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations. CoRR David Krueger, Tegan Maharaj, János Kramár, Mohammad Pezeshki, Nicolas Ballas, Nan Rosemary Ke, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Aaron C. Courville, Chris Pal
2015	J	`jnl`	Stories in the Eye: Contextual Visual Interactions for Efficient Video to Language Translation. CoRR Anirudh Goyal, Marius Leordeanu
2014	—	`conf`	Monocular vision based road marking recognition for driver assistance and safety. ICVES Mohak Sukhwani, Suriya Singh, Anirudh Goyal, Aseem Behl, Pritish Mohapatra, Brijendra Kumar Bharti, C. V. Jawahar