Lamb, Alex

25 publications

ICLR 2025 The Belief State Transformer Edward S. Hu, Kwangjun Ahn, Qinghua Liu, Haoran Xu, Manan Tomar, Ada Langford, Dinesh Jayaraman, Alex Lamb, John Langford

ICLR 2025 Towards Improving Exploration Through Sibling Augmented GFlowNets Kanika Madan, Alex Lamb, Emmanuel Bengio, Glen Berseth, Yoshua Bengio

ICML 2024 PcLast: Discovering Plannable Continuous Latent States Anurag Koul, Shivakanth Sujit, Shaoru Chen, Ben Evans, Lili Wu, Byron Xu, Rajan Chari, Riashat Islam, Raihan Seraj, Yonathan Efroni, Lekan P Molu, Miroslav Dudı́k, John Langford, Alex Lamb

ICLR 2024 Towards Principled Representation Learning from Videos for Reinforcement Learning Dipendra Misra, Akanksha Saran, Tengyang Xie, Alex Lamb, John Langford

NeurIPSW 2024 Towards Principled Representation Learning from Videos for Reinforcement Learning Dipendra Misra, Akanksha Saran, Tengyang Xie, Alex Lamb, John Langford

AAAI 2023 Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization for Heterogeneous Representational Coarseness Dianbo Liu, Alex Lamb, Xu Ji, Pascal Tikeng Notsawo Jr., Michael Mozer, Yoshua Bengio, Kenji Kawaguchi

NeurIPSW 2023 Agent-Centric State Discovery for Finite-Memory POMDPs Lili Wu, Ben Evans, Riashat Islam, Raihan Seraj, Yonathan Efroni, Alex Lamb

TMLR 2023 Guaranteed Discovery of Control-Endogenous Latent States with Multi-Step Inverse Models Alex Lamb, Riashat Islam, Yonathan Efroni, Aniket Rajiv Didolkar, Dipendra Misra, Dylan J Foster, Lekan P Molu, Rajan Chari, Akshay Krishnamurthy, John Langford

ICML 2023 Principled Offline RL in the Presence of Rich Exogenous Information Riashat Islam, Manan Tomar, Alex Lamb, Yonathan Efroni, Hongyu Zang, Aniket Rajiv Didolkar, Dipendra Misra, Xin Li, Harm Van Seijen, Remi Tachet Des Combes, John Langford

AISTATS 2023 Representation Learning in Deep RL via Discrete Information Bottleneck Riashat Islam, Hongyu Zang, Manan Tomar, Aniket Didolkar, Md Mofijul Islam, Samin Yeasar Arnob, Tariq Iqbal, Xin Li, Anirudh Goyal, Nicolas Heess, Alex Lamb

NeurIPSW 2022 Agent-Controller Representations: Principled Offline RL with Rich Exogenous Information Riashat Islam, Manan Tomar, Alex Lamb, Hongyu Zang, Yonathan Efroni, Dipendra Misra, Aniket Rajiv Didolkar, Xin Li, Harm van Seijen, Remi Tachet des Combes, John Langford

ICLR 2022 Coordination Among Neural Modules Through a Shared Global Workspace Anirudh Goyal, Aniket Rajiv Didolkar, Alex Lamb, Kartikeya Badola, Nan Rosemary Ke, Nasim Rahaman, Jonathan Binas, Charles Blundell, Michael Curtis Mozer, Yoshua Bengio

NeurIPSW 2022 Towards Data-Driven Offline Simulations for Online Reinforcement Learning Shengpu Tang, Felipe Vieira Frujeri, Dipendra Misra, Alex Lamb, John Langford, Paul Mineiro, Sebastian Kochman

AISTATS 2021 Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information Across Layers Alex Lamb, Anirudh Goyal, Agnieszka Słowik, Michael Mozer, Philippe Beaudoin, Yoshua Bengio

NeurIPSW 2021 Catastrophic Failures of Neural Active Learning on Heteroskedastic Distributions Savya Khosla, Alex Lamb, Jordan T. Ash, Cyril Zhang, Kenji Kawaguchi

ICLR 2021 Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Charles Blundell, Sergey Levine, Yoshua Bengio, Michael Curtis Mozer

AAAI 2021 GraphMix: Improved Training of GNNs for Semi-Supervised Learning Vikas Verma, Meng Qu, Kenji Kawaguchi, Alex Lamb, Yoshua Bengio, Juho Kannala, Jian Tang

ICLR 2021 Recurrent Independent Mechanisms Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schölkopf

ICML 2020 Learning to Combine Top-Down and Bottom-up Signals in Recurrent Neural Networks with Attention over Modules Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio

WACV 2020 SketchTransfer: A New Dataset for Exploring Detail-Invariance and the Abstractions Learned by Deep Networks Alex Lamb, Sherjil Ozair, Vikas Verma, David Ha

ICLRW 2019 Adversarial Mixup Resynthesizers Christopher Beckham, Sina Honari, Alex Lamb, Vikas Verma, Farnoosh Ghadiri, R Devon Hjelm, Christopher Pal

IJCAI 2019 Interpolation Consistency Training for Semi-Supervised Learning Vikas Verma, Alex Lamb, Juho Kannala, Yoshua Bengio, David Lopez-Paz

ICML 2019 Manifold Mixup: Better Representations by Interpolating Hidden States Vikas Verma, Alex Lamb, Christopher Beckham, Amir Najafi, Ioannis Mitliagkas, David Lopez-Paz, Yoshua Bengio

ICML 2019 State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations Alex Lamb, Jonathan Binas, Anirudh Goyal, Sandeep Subramanian, Ioannis Mitliagkas, Yoshua Bengio, Michael Mozer

ICLR 2017 Adversarially Learned Inference Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Alex Lamb, Martín Arjovsky, Olivier Mastropietro, Aaron C. Courville