Anirudh Goyal

Most-cited papers

Toward Causal Representation Learning
B. Schölkopf, Francesco Locatello, Stefan Bauer, N. Ke +3 more
2021Proceedings of the IEEE1,713 citations Open access
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Professor Forcing: A New Algorithm for Training Recurrent Networks
Alex Lamb, Anirudh Goyal, Ying Zhang, Sai-Zheng Zhang +2 more
2016Neural Information Processing Systems722 citations
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An Actor-Critic Algorithm for Sequence Prediction
D. Bahdanau, Philémon Brakel, Kelvin Xu, Anirudh Goyal +4 more
2016International Conference on Learning Representations680 citations
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Inductive biases for deep learning of higher-level cognition
Anirudh Goyal, Yoshua Bengio
2020Proceedings of the Royal Society A498 citations Open access
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A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms
Yoshua Bengio, T. Deleu, Nasim Rahaman, N. Ke +4 more
2019International Conference on Learning Representations389 citations
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Recurrent Independent Mechanisms
Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani +3 more
2019International Conference on Learning Representations374 citations
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Towards Causal Representation Learning
B. Schölkopf, Francesco Locatello, Stefan Bauer, N. Ke +3 more
2021arXiv.org369 citations
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Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations
D. Krueger, Tegan Maharaj, J'anos Kram'ar, M. Pezeshki +7 more
2016International Conference on Learning Representations335 citations
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Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning
Yuxi Xie, Anirudh Goyal, Wenyue Zheng, Min-Yen Kan +3 more
2024arXiv.org268 citations
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Z-Forcing: Training Stochastic Recurrent Networks
Anirudh Goyal, A. Sordoni, Marc-Alexandre Côté, N. Ke +1 more
2017Neural Information Processing Systems199 citations
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Learning Neural Causal Models from Unknown Interventions
N. Ke, O. Bilaniuk, Anirudh Goyal, Stefan Bauer +3 more
2019arXiv.org192 citations
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InfoBot: Transfer and Exploration via the Information Bottleneck
Anirudh Goyal, Riashat Islam, D. Strouse, Zafarali Ahmed +4 more
2019International Conference on Learning Representations192 citations
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On Disentangled Representations Learned from Correlated Data
Frederik Trauble, Elliot Creager, Niki Kilbertus, Francesco Locatello +4 more
2020International Conference on Machine Learning144 citations
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Keeping LLMs Aligned After Fine-tuning: The Crucial Role of Prompt Templates
Kaifeng Lyu, Hao-Yu Zhao, Xin-Ran Gu, Ding-Li Yu +2 more
2024Neural Information Processing Systems134 citations
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A Theory for Emergence of Complex Skills in Language Models
Sanjeev Arora, Anirudh Goyal
2023arXiv.org129 citations Open access
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Maximum Entropy Generators for Energy-Based Models
Rithesh Kumar, Anirudh Goyal, Aaron C. Courville, Yoshua Bengio
2019arXiv.org120 citations
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Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving
A. Didolkar, Anirudh Goyal, N. Ke, Si-Yuan Guo +6 more
2024Neural Information Processing Systems103 citations
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Sparse Attentive Backtracking: Temporal CreditAssignment Through Reminding
N. Ke, Anirudh Goyal, O. Bilaniuk, Jonathan Binas +3 more
2018Neural Information Processing Systems97 citations
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Small-GAN: Speeding Up GAN Training Using Core-sets
Samarth Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio +2 more
2019International Conference on Machine Learning93 citations
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Learning to Induce Causal Structure
N. Ke, S. Chiappa, Jane X. Wang, J. Bornschein +6 more
2022International Conference on Learning Representations86 citations Open access
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Skill-Mix: a Flexible and Expandable Family of Evaluations for AI models
Ding-Li Yu, Simran Kaur, Arushi Gupta, Jonah Brown-Cohen +2 more
2023International Conference on Learning Representations79 citations
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Retrieval-Augmented Reinforcement Learning
Anirudh Goyal, A. Friesen, Andrea Banino, T. Weber +12 more
2022International Conference on Machine Learning79 citations
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Recall Traces: Backtracking Models for Efficient Reinforcement Learning
Anirudh Goyal, Philémon Brakel, W. Fedus, Soumye Singhal +4 more
2018International Conference on Learning Representations70 citations
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Variational Causal Networks: Approximate Bayesian Inference over Causal Structures
Yashas Annadani, Jonas Rothfuss, Alexandre Lacoste, Nino Scherrer +3 more
2021arXiv.org65 citations
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Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net
Anirudh Goyal, N. Ke, S. Ganguli, Yoshua Bengio
2017Neural Information Processing Systems57 citations
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Learning Neural Causal Models with Active Interventions
Nino Scherrer, O. Bilaniuk, Yashas Annadani, Anirudh Goyal +6 more
2021arXiv.org56 citations
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Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives
Anirudh Goyal, Shagun Sodhani, Jonathan Binas, Xue-Bin Peng +2 more
2019International Conference on Learning Representations55 citations
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Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future
N. Ke, Amanpreet Singh, Ahmed Touati, Anirudh Goyal +3 more
2019arXiv.org55 citations
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Accelerating Greedy Coordinate Gradient and General Prompt Optimization via Probe Sampling
Yiran Zhao, Wenyue Zheng, Tianle Cai, Do Xuan Long +3 more
2024Neural Information Processing Systems49 citations Open access
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Learning by Directional Gradient Descent
David Silver, Anirudh Goyal, I. Danihelka, Matteo Hessel +1 more
2022International Conference on Learning Representations49 citations
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AI-Assisted Generation of Difficult Math Questions
Vedant Shah, Ding-Li Yu, Kaifeng Lyu, Simon Park +7 more
2024arXiv.org48 citations
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Fortified Networks: Improving the Robustness of Deep Networks by Modeling the Manifold of Hidden Representations
Alex Lamb, Jonathan Binas, Anirudh Goyal, Dmitriy Serdyuk +3 more
2018arXiv.org46 citations
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DIBS: Diversity inducing Information Bottleneck in Model Ensembles
Samarth Sinha, Homanga Bharadhwaj, Anirudh Goyal, H. Larochelle +2 more
2020AAAI Conference on Artificial Intelligence45 citations Open access
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Fast and Slow Learning of Recurrent Independent Mechanisms
Kanika Madan, N. Ke, Anirudh Goyal, Bernhard Schölkopf +1 more
2021International Conference on Learning Representations44 citations
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Generalization of Equilibrium Propagation to Vector Field Dynamics
B. Scellier, Anirudh Goyal, Jonathan Binas, Thomas Mesnard +1 more
2018arXiv.org43 citations
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Modeling the Long Term Future in Model-Based Reinforcement Learning
N. Ke, Amanpreet Singh, Ahmed Touati, Anirudh Goyal +3 more
2018International Conference on Learning Representations40 citations
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Instruct-SkillMix: A Powerful Pipeline for LLM Instruction Tuning
Simran Kaur, Simon Park, Anirudh Goyal, Sanjeev Arora
2024arXiv.org33 citations
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GFlowOut: Dropout with Generative Flow Networks
Dian-Bo Liu, Moksh Jain, Bonaventure F. P. Dossou, Qianli Shen +9 more
2022International Conference on Machine Learning28 citations Open access
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Discrete Key-Value Bottleneck
Frederik Trauble, Anirudh Goyal, Nasim Rahaman, M. Mozer +3 more
2022International Conference on Machine Learning26 citations Open access
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The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget
Anirudh Goyal, Yoshua Bengio, M. Botvinick, S. Levine
2020International Conference on Learning Representations26 citations
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Zero-Shot Object-Centric Representation Learning
A. Didolkar, Andrii Zadaianchuk, Anirudh Goyal, M. Mozer +3 more
2024arXiv.org25 citations
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Transformers with Competitive Ensembles of Independent Mechanisms
Alex Lamb, Di He, Anirudh Goyal, Guolin Ke +3 more
2021arXiv.org25 citations
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Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning
Y. Bengio, A. Didolkar, Anirudh Goyal, Nitesh Bharadwaj Gundavarapu +3 more
2022Neural Information Processing Systems24 citations Open access
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Can Models Learn Skill Composition from Examples?
Hao-Yu Zhao, Simran Kaur, Ding-Li Yu, Anirudh Goyal +1 more
2024Neural Information Processing Systems21 citations
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Untangling tradeoffs between recurrence and self-attention in artificial neural networks
Giancarlo Kerg, Bhargav Kanuparthi, Anirudh Goyal, Kyle Goyette +2 more
2020Neural Information Processing Systems16 citations
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Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments
Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin +4 more
2021International Conference on Learning Representations15 citations
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Extending the Framework of Equilibrium Propagation to General Dynamics
B. Scellier, Anirudh Goyal, Jonathan Binas, Thomas Mesnard +1 more
2018International Conference on Learning Representations15 citations
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Sparse Attentive Backtracking: Long-Range Credit Assignment in Recurrent Networks
N. Ke, Anirudh Goyal, O. Bilaniuk, Jonathan Binas +3 more
2017arXiv.org15 citations
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On the Transfer of Object-Centric Representation Learning
A. Didolkar, Andrii Zadaianchuk, Anirudh Goyal, M. Mozer +3 more
2025International Conference on Learning Representations14 citations
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Unlearning via Sparse Representations
Vedant Shah, Frederik Trauble, A. Malik, Hugo Larochelle +4 more
2023Trans. Mach. Learn. Res.14 citations
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