Alex Lamb

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 68

Top Topics

Procedural Knowledge

Supervised Learning

Vector Quantization

Top Venues

Publications

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)
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)
Anurag Koul, Shivakanth Sujit, Shaoru Chen, Ben Evans, Lili Wu, Byron Xu, Rajan Chari, Riashat Islam, Raihan Seraj, Yonathan Efroni, Lekan P. Molu, Miro Dudík, John Langford, Alex Lamb
PcLast: Discovering Plannable Continuous Latent States. CoRR (2023)
Alex Lamb, Riashat Islam, Yonathan Efroni, Aniket Rajiv Didolkar, Dipendra Misra, Dylan J. Foster, Lekan P. Molu, Rajan Chari, Akshay Krishnamurthy, John Langford
Guaranteed Discovery of Control-Endogenous Latent States with Multi-Step Inverse Models. Trans. Mach. Learn. Res. 2023 (2023)
Dianbo Liu, Alex Lamb, Xu Ji, Pascal Tikeng Notsawo Jr., Michael Mozer, Yoshua Bengio, Kenji Kawaguchi
Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization for Heterogeneous Representational Coarseness. AAAI (2023)
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
Principled Offline RL in the Presence of Rich Exogenous Information. ICML (2023)
Savya Khosla, Chew Kin Whye, Jordan T. Ash, Cyril Zhang, Kenji Kawaguchi, Alex Lamb
Understanding and Improving Neural Active Learning on Heteroskedastic Distributions. ECAI (2023)
Alex Lamb, Riashat Islam, Yonathan Efroni, Aniket Didolkar, Dipendra Misra, Dylan J. Foster, Lekan Molu, Rajan Chari, Akshay Krishnamurthy, John Langford
Guaranteed Discovery of Controllable Latent States with Multi-Step Inverse Models. CoRR (2022)
Vikas Verma, Kenji Kawaguchi, Alex Lamb, Juho Kannala, Arno Solin, Yoshua Bengio, David Lopez-Paz
Interpolation consistency training for semi-supervised learning. Neural Networks 145 (2022)
Riashat Islam, Manan Tomar, Alex Lamb, Yonathan Efroni, Hongyu Zang, Aniket Didolkar, Dipendra Misra, Xin Li, Harm van Seijen, Remi Tachet des Combes, John Langford
Agent-Controller Representations: Principled Offline RL with Rich Exogenous Information. 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)
Alexia Jolicoeur-Martineau, Alex Lamb, Vikas Verma, Aniket Didolkar
CNT (Conditioning on Noisy Targets): A new Algorithm for Leveraging Top-Down Feedback. CoRR (2022)
Shengpu Tang, Felipe Vieira Frujeri, Dipendra Misra, Alex Lamb, John Langford, Paul Mineiro, Sebastian Kochman
Towards Data-Driven Offline Simulations for Online Reinforcement Learning. 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)
Alex Lamb, Vikas Verma, Kenji Kawaguchi, Alexander Matyasko, Savya Khosla, Juho Kannala, Yoshua Bengio
Interpolated Adversarial Training: Achieving robust neural networks without sacrificing too much accuracy. Neural Networks 154 (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)
Savya Khosla, Chew Kin Whye, Jordan T. Ash, Cyril Zhang, Kenji Kawaguchi, Alex Lamb
Neural Active Learning on Heteroskedastic Distributions. CoRR (2022)
Dianbo Liu, Alex Lamb, Xu Ji, Pascal Notsawo, Michael Mozer, Yoshua Bengio, Kenji Kawaguchi
Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization. CoRR (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)
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)
Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael Curtis Mozer, Yoshua Bengio
Discrete-Valued Neural Communication. CoRR (2021)
Alex Lamb
A Brief Introduction to Generative Models. CoRR (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)
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)
Vikas Verma, Meng Qu, Kenji Kawaguchi, Alex Lamb, Yoshua Bengio, Juho Kannala, Jian Tang
GraphMix: Improved Training of GNNs for Semi-Supervised Learning. 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)
Alex Lamb, Tarin Clanuwat, Siyu Han, Mikel Bober-Irizar, Asanobu Kitamoto
Predicting the Ordering of Characters in Japanese Historical Documents. CoRR (2021)
Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael C. Mozer, Yoshua Bengio
Discrete-Valued Neural Communication. NeurIPS (2021)
Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schölkopf
Recurrent Independent Mechanisms. ICLR (2021)
Yingtao Tian, Chikahiko Suzuki, Tarin Clanuwat, Mikel Bober-Irizar, Alex Lamb, Asanobu Kitamoto
KaoKore: A Pre-modern Japanese Art Facial Expression Dataset. CoRR (2020)
Alex Lamb, Tarin Clanuwat, Asanobu Kitamoto
KuroNet: Regularized Residual U-Nets for End-to-End Kuzushiji Character Recognition. SN Comput. Sci. 1 (3) (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)
Saeid Asgari Taghanaki, Mohammad Havaei, Alex Lamb, Aditya Sanghi, Ara Danielyan, Tonya Custis
Jigsaw-VAE: Towards Balancing Features in Variational Autoencoders. CoRR (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)
Alex Lamb, Sherjil Ozair, Vikas Verma, David Ha
SketchTransfer: A Challenging New Task for Exploring Detail-Invariance and the Abstractions Learned by Deep Networks. WACV (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)
Yingtao Tian, Chikahiko Suzuki, Tarin Clanuwat, Mikel Bober-Irizar, Alex Lamb, Asanobu Kitamoto
KaoKore: A Pre-modern Japanese Art Facial Expression Dataset. ICCC (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)
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)
Alex Lamb, Sherjil Ozair, Vikas Verma, David Ha
SketchTransfer: A Challenging New Task for Exploring Detail-Invariance and the Abstractions Learned by Deep Networks. CoRR (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)
Vikas Verma, Alex Lamb, Christopher Beckham, Amir Najafi, Ioannis Mitliagkas, David Lopez-Paz, Yoshua Bengio
Manifold Mixup: Better Representations by Interpolating Hidden States. ICML (2019)
Vikas Verma, Alex Lamb, Juho Kannala, Yoshua Bengio, David Lopez-Paz
Interpolation Consistency Training for Semi-Supervised Learning. CoRR (2019)
Christopher Beckham, Sina Honari, Vikas Verma, Alex Lamb, Farnoosh Ghadiri, R. Devon Hjelm, Yoshua Bengio, Chris Pal
On Adversarial Mixup Resynthesis. NeurIPS (2019)
Vikas Verma, Alex Lamb, Juho Kannala, Yoshua Bengio, David Lopez-Paz
Interpolation Consistency Training for Semi-supervised Learning. IJCAI (2019)
Tarin Clanuwat, Alex Lamb, Asanobu Kitamoto
KuroNet: Pre-Modern Japanese Kuzushiji Character Recognition with Deep Learning. CoRR (2019)
Alex Lamb, Vikas Verma, Juho Kannala, Yoshua Bengio
Interpolated Adversarial Training: Achieving Robust Neural Networks Without Sacrificing Too Much Accuracy. AISec@CCS (2019)
Vikas Verma, Meng Qu, Alex Lamb, Yoshua Bengio, Juho Kannala, Jian Tang
GraphMix: Regularized Training of Graph Neural Networks for Semi-Supervised Learning. CoRR (2019)
Alex Lamb, Vikas Verma, Juho Kannala, Yoshua Bengio
Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Accuracy. CoRR (2019)
Christopher Beckham, Sina Honari, Alex Lamb, Vikas Verma, Farnoosh Ghadiri, R. Devon Hjelm, Christopher J. Pal
Adversarial Mixup Resynthesizers. DGS@ICLR (2019)
Christopher Beckham, Sina Honari, Alex Lamb, Vikas Verma, Farnoosh Ghadiri, R. Devon Hjelm, Christopher J. Pal
Adversarial Mixup Resynthesizers. CoRR (2019)
Tarin Clanuwat, Alex Lamb, Asanobu Kitamoto
KuroNet: Pre-Modern Japanese Kuzushiji Character Recognition with Deep Learning. ICDAR (2019)
Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, Bernhard Schölkopf
Recurrent Independent Mechanisms. CoRR (2019)
Alex Lamb, Jonathan Binas, Anirudh Goyal, Dmitriy Serdyuk, Sandeep Subramanian, Ioannis Mitliagkas, Yoshua Bengio
Fortified Networks: Improving the Robustness of Deep Networks by Modeling the Manifold of Hidden Representations. CoRR (2018)
Vikas Verma, Alex Lamb, Christopher Beckham, Aaron C. Courville, Ioannis Mitliagkas, Yoshua Bengio
Manifold Mixup: Encouraging Meaningful On-Manifold Interpolation as a Regularizer. CoRR (2018)
Tarin Clanuwat, Mikel Bober-Irizar, Asanobu Kitamoto, Alex Lamb, Kazuaki Yamamoto, David Ha
Deep Learning for Classical Japanese Literature. CoRR (2018)
Alex Lamb, R. Devon Hjelm, Yaroslav Ganin, Joseph Paul Cohen, Aaron C. Courville, Yoshua Bengio
GibbsNet: Iterative Adversarial Inference for Deep Graphical Models. CoRR (2017)
Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Alex Lamb, Martín Arjovsky, Olivier Mastropietro, Aaron C. Courville
Adversarially Learned Inference. ICLR (Poster) (2017)
Alex Lamb, R. Devon Hjelm, Yaroslav Ganin, Joseph Paul Cohen, Aaron C. Courville, Yoshua Bengio
GibbsNet: Iterative Adversarial Inference for Deep Graphical Models. NIPS (2017)
Anirudh Goyal, Nan Rosemary Ke, Alex Lamb, R. Devon Hjelm, Chris Pal, Joelle Pineau, Yoshua Bengio
ACtuAL: Actor-Critic Under Adversarial Learning. CoRR (2017)
Anirudh Goyal, Alex Lamb, Ying Zhang, Saizheng Zhang, Aaron C. Courville, Yoshua Bengio
Professor Forcing: A New Algorithm for Training Recurrent Networks. NIPS (2016)
Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Alex Lamb, Martín Arjovsky, Olivier Mastropietro, Aaron C. Courville
Adversarially Learned Inference. CoRR (2016)
Alex Lamb, Anirudh Goyal, Ying Zhang, Saizheng Zhang, Aaron C. Courville, Yoshua Bengio
Professor Forcing: A New Algorithm for Training Recurrent Networks. CoRR (2016)
Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermüller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, Yoshua Bengio, Arnaud Bergeron, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul F. Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron C. Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Melanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian J. Goodfellow, Matthew Graham, Çaglar Gülçehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrançois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Joseph Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph P. Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang
Theano: A Python framework for fast computation of mathematical expressions. CoRR (2016)
Alex Lamb, Vincent Dumoulin, Aaron C. Courville
Discriminative Regularization for Generative Models. CoRR (2016)
Guillaume Alain, Alex Lamb, Chinnadhurai Sankar, Aaron C. Courville, Yoshua Bengio
Variance Reduction in SGD by Distributed Importance Sampling. CoRR (2015)
Alex Lamb, Michael J. Paul, Mark Dredze
Separating Fact from Fear: Tracking Flu Infections on Twitter. HLT-NAACL (2013)
Alex Lamb, Michael J. Paul, Mark Dredze
Investigating Twitter as a Source for Studying Behavioral Responses to Epidemics. AAAI Fall Symposium: Information Retrieval and Knowledge Discovery in Biomedical Text (2012)