Nan Rosemary Ke

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 64

Top Topics

Recurrent Networks

Reinforcement Learning

Credit Assignment

Top Venues

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)
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)
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)
SIMA Team, Maria Abi Raad, Arun Ahuja, Catarina Barros, Frederic Besse, Andrew Bolt, Adrian Bolton, Bethanie Brownfield, Gavin Buttimore, Max Cant, Sarah Chakera, Stephanie C. Y. Chan, Jeff Clune, Adrian Collister, Vikki Copeman, Alex Cullum, Ishita Dasgupta, Dario de Cesare, Julia Di Trapani, Yani Donchev, Emma Dunleavy, Martin Engelcke, Ryan Faulkner, Frankie Garcia, Charles Gbadamosi, Zhitao Gong, Lucy Gonzalez, Kshitij Gupta, Karol Gregor, Arne Olav Hallingstad, Tim Harley, Sam Haves, Felix Hill, Ed Hirst, Drew A. Hudson, Jony Hudson, Steph Hughes-Fitt, Danilo J. Rezende, Mimi Jasarevic, Laura Kampis, Nan Rosemary Ke, Thomas Keck, Junkyung Kim, Oscar Knagg, Kavya Kopparapu, Andrew K. Lampinen, Shane Legg, Alexander Lerchner, Marjorie Limont, Yulan Liu, Maria Loks-Thompson, Joseph Marino, Kathryn Martin Cussons, Loic Matthey, Siobhan Mcloughlin, Piermaria Mendolicchio, Hamza Merzic, Anna Mitenkova, Alexandre Moufarek, Valéria Oliveira, Yanko Gitahy Oliveira, Hannah Openshaw, Renke Pan, Aneesh Pappu, Alex Platonov, Ollie Purkiss, David P. Reichert, John Reid, Pierre Harvey Richemond, Tyson Roberts, Giles Ruscoe, Jaume Sanchez Elias, Tasha Sandars, Daniel P. Sawyer, Tim Scholtes, Guy Simmons, Daniel Slater, Hubert Soyer, Heiko Strathmann, Peter Stys, Allison C. Tam, Denis Teplyashin, Tayfun Terzi, Davide Vercelli, Bojan Vujatovic, Marcus Wainwright, Jane X. Wang, Zhengdong Wang, Daan Wierstra, Duncan Williams, Nathaniel Wong, Sarah York, Nick Young
Scaling Instructable Agents Across Many Simulated Worlds. CoRR (2024)
Eliza Kosoy, David M. Chan, Adrian Liu, Jasmine Collins, Jessica B. Hamrick, Sandy Han Huang, Nan Rosemary Ke, Emily Rose Reagan, John F. Canny, Alison Gopnik
Towards Understanding How Machines Can Learn Causal Overhypotheses. CogSci (2023)
Chentian Jiang, Nan Rosemary Ke, Hado van Hasselt
Learning How to Infer Partial MDPs for In-Context Adaptation and Exploration. 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)
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)
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)
Eliza Kosoy, David M. Chan, Adrian Liu, Jasmine Collins, Bryanna Kaufmann, Sandy Han Huang, Jessica B. Hamrick, John F. Canny, Nan Rosemary Ke, Alison Gopnik
Towards Understanding How Machines Can Learn Causal Overhypotheses. CoRR (2022)
Nino Scherrer, Anirudh Goyal, Stefan Bauer, Yoshua Bengio, Nan Rosemary Ke
On the Generalization and Adaption Performance of Causal Models. 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)
Eliza Kosoy, Adrian Liu, Jasmine Collins, David M. Chan, Jessica B. Hamrick, Nan Rosemary Ke, Sandy H. Huang, Bryanna Kaufmann, John F. Canny, Alison Gopnik
Learning Causal Overhypotheses through Exploration in Children and Computational Models. 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)
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)
Eliza Kosoy, Adrian Liu, Jasmine Collins, David M. Chan, Jessica B. Hamrick, Sandy Han Huang, Nan Rosemary Ke, Bryanna Kaufmann, Alison Gopnik
Learning Causal Overhypotheses through Exploration in Children and Computational Models. CogSci (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)
Eliza Kosoy, Adrian Liu, Jasmine Collins, David M. Chan, Jessica B. Hamrick, Nan Rosemary Ke, Sandy H. Huang, Bryanna Kaufmann, John F. Canny, Alison Gopnik
Learning Causal Overhypotheses through Exploration in Children and Computational Models. CLeaR (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)
Ignavier Ng, Sébastien Lachapelle, Nan Rosemary Ke, Simon Lacoste-Julien, Kun Zhang
On the Convergence of Continuous Constrained Optimization for Structure Learning. AISTATS (2022)
Jithendaraa Subramanian, Yashas Annadani, Ivaxi Sheth, Nan Rosemary Ke, Tristan Deleu, Stefan Bauer, Derek Nowrouzezahrai, Samira Ebrahimi Kahou
Learning Latent Structural Causal Models. CoRR (2022)
Kanika Madan, Nan Rosemary Ke, Anirudh Goyal, Bernhard Schölkopf, Yoshua Bengio
Fast And Slow Learning Of Recurrent Independent Mechanisms. 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)
Jörg Bornschein, Silvia Chiappa, Alan Malek, Nan Rosemary Ke
Prequential MDL for Causal Structure Learning with Neural Networks. CoRR (2021)
Kanika Madan, Nan Rosemary Ke, Anirudh Goyal, Bernhard Schölkopf, Yoshua Bengio
Fast and Slow Learning of Recurrent Independent Mechanisms. 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)
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)
Bernhard Schölkopf, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke, Nal Kalchbrenner, Anirudh Goyal, Yoshua Bengio
Toward Causal Representation Learning. Proc. IEEE 109 (5) (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)
Nan Rosemary Ke, Jane X. Wang, Jovana Mitrovic, Martin Szummer, Danilo J. Rezende
Amortized learning of neural causal representations. CoRR (2020)
Danilo J. Rezende, Ivo Danihelka, George Papamakarios, Nan Rosemary Ke, Ray Jiang, Theophane Weber, Karol Gregor, Hamza Merzic, Fabio Viola, Jane Wang, Jovana Mitrovic, Frederic Besse, Ioannis Antonoglou, Lars Buesing
Causally Correct Partial Models for Reinforcement Learning. CoRR (2020)
Ignavier Ng, Sébastien Lachapelle, Nan Rosemary Ke, Simon Lacoste-Julien
On the Convergence of Continuous Constrained Optimization for Structure Learning. CoRR (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)
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)
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)
Nan Rosemary Ke, Amanpreet Singh, Ahmed Touati, Anirudh Goyal, Yoshua Bengio, Devi Parikh, Dhruv Batra
Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future. CoRR (2019)
Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Chris Pal, Yoshua Bengio
Learning Neural Causal Models from Unknown Interventions. CoRR (2019)
Bhargav Kanuparthi, Devansh Arpit, Giancarlo Kerg, Nan Rosemary Ke, Ioannis Mitliagkas, Yoshua Bengio
h-detach: Modifying the LSTM Gradient Towards Better Optimization. ICLR (Poster) (2019)
Nan Rosemary Ke, Anirudh Goyal, Olexa Bilaniuk, Jonathan Binas, Michael C. Mozer, Chris Pal, Yoshua Bengio
Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding. NeurIPS (2018)
Peter Henderson, Koustuv Sinha, Nan Rosemary Ke, Joelle Pineau
Adversarial Gain. CoRR (2018)
Peter Henderson, Koustuv Sinha, Nicolas Angelard-Gontier, Nan Rosemary Ke, Genevieve Fried, Ryan Lowe, Joelle Pineau
Ethical Challenges in Data-Driven Dialogue Systems. AIES (2018)
Nan Rosemary Ke, Konrad Zolna, Alessandro Sordoni, Zhouhan Lin, Adam Trischler, Yoshua Bengio, Joelle Pineau, Laurent Charlin, Christopher J. Pal
Focused Hierarchical RNNs for Conditional Sequence Processing. ICML (2018)
Dmitriy Serdyuk, Nan Rosemary Ke, Alessandro Sordoni, Adam Trischler, Chris Pal, Yoshua Bengio
Twin Networks: Matching the Future for Sequence Generation. ICLR (Poster) (2018)
Nan Rosemary Ke, Konrad Zolna, Alessandro Sordoni, Zhouhan Lin, Adam Trischler, Yoshua Bengio, Joelle Pineau, Laurent Charlin, Chris Pal
Focused Hierarchical RNNs for Conditional Sequence Processing. CoRR (2018)
Iulian Vlad Serban, Chinnadhurai Sankar, Mathieu Germain, Saizheng Zhang, Zhouhan Lin, Sandeep Subramanian, Taesup Kim, Michael Pieper, Sarath Chandar, Nan Rosemary Ke, Sai Rajeswar, Alexandre de Brébisson, Jose M. R. Sotelo, Dendi Suhubdy, Vincent Michalski, Alexandre Nguyen, Joelle Pineau, Yoshua Bengio
A Deep Reinforcement Learning Chatbot (Short Version). CoRR (2018)
Devansh Arpit, Bhargav Kanuparthi, Giancarlo Kerg, Nan Rosemary Ke, Ioannis Mitliagkas, Yoshua Bengio
h-detach: Modifying the LSTM Gradient Towards Better Optimization. CoRR (2018)
Nan Rosemary Ke, Anirudh Goyal, Olexa Bilaniuk, Jonathan Binas, Michael C. Mozer, Chris Pal, Yoshua Bengio
Sparse Attentive Backtracking: Temporal CreditAssignment Through Reminding. CoRR (2018)
Anirudh Goyal, Alessandro Sordoni, Marc-Alexandre Côté, Nan Rosemary Ke, Yoshua Bengio
Z-Forcing: Training Stochastic Recurrent Networks. CoRR (2017)
Nan Rosemary Ke, Anirudh Goyal, Olexa Bilaniuk, Jonathan Binas, Laurent Charlin, Chris Pal, Yoshua Bengio
Sparse Attentive Backtracking: Long-Range Credit Assignment in Recurrent Networks. CoRR (2017)
Dmitriy Serdyuk, Nan Rosemary Ke, Alessandro Sordoni, Chris Pal, Yoshua Bengio
Twin Networks: Using the Future as a Regularizer. CoRR (2017)
Anirudh Goyal, Nan Rosemary Ke, Surya Ganguli, Yoshua Bengio
Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net. NIPS (2017)
Anirudh Goyal, Nan Rosemary Ke, Surya Ganguli, Yoshua Bengio
Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net. CoRR (2017)
Anirudh Goyal, Alessandro Sordoni, Marc-Alexandre Côté, Nan Rosemary Ke, Yoshua Bengio
Z-Forcing: Training Stochastic Recurrent Networks. 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)
Iulian Vlad Serban, Chinnadhurai Sankar, Mathieu Germain, Saizheng Zhang, Zhouhan Lin, Sandeep Subramanian, Taesup Kim, Michael Pieper, Sarath Chandar, Nan Rosemary Ke, Sai Mudumba, Alexandre de Brébisson, Jose Sotelo, Dendi Suhubdy, Vincent Michalski, Alexandre Nguyen, Joelle Pineau, Yoshua Bengio
A Deep Reinforcement Learning Chatbot. CoRR (2017)
David Krueger, Tegan Maharaj, János Kramár, Mohammad Pezeshki, Nicolas Ballas, Nan Rosemary Ke, Anirudh Goyal, Yoshua Bengio, Aaron C. Courville, Christopher J. Pal
Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations. ICLR (Poster) (2017)
Peter Henderson, Koustuv Sinha, Nicolas Angelard-Gontier, Nan Rosemary Ke, Genevieve Fried, Ryan Lowe, Joelle Pineau
Ethical Challenges in Data-Driven Dialogue Systems. CoRR (2017)
David Krueger, Tegan Maharaj, János Kramár, Mohammad Pezeshki, Nicolas Ballas, Nan Rosemary Ke, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Aaron C. Courville, Chris Pal
Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations. CoRR (2016)
Shi Zong, Hao Ni, Kenny Sung, Nan Rosemary Ke, Zheng Wen, Branislav Kveton
Cascading Bandits for Large-Scale Recommendation Problems. CoRR (2016)
Shi Zong, Hao Ni, Kenny Sung, Nan Rosemary Ke, Zheng Wen, Branislav Kveton
Cascading Bandits for Large-Scale Recommendation Problems. UAI (2016)
William Chan, Nan Rosemary Ke, Ian R. Lane
Transferring Knowledge from a RNN to a DNN. CoRR (2015)
William Chan, Nan Rosemary Ke, Ian R. Lane
Transferring knowledge from a RNN to a DNN. INTERSPEECH (2015)
Dzmitry Bahdanau, Dmitriy Serdyuk, Philemon Brakel, Nan Rosemary Ke, Jan Chorowski, Aaron C. Courville, Yoshua Bengio
Task Loss Estimation for Sequence Prediction. CoRR (2015)
Konstantin Schauwecker, Nan Rosemary Ke, Sebastian A. Scherer, Andreas Zell
Markerless Visual Control of a Quad-Rotor Micro Aerial Vehicle by Means of On-Board Stereo Processing. AMS (2012)
Aniruddh Gandhi, Nan Rosemary Ke, Bakhadyr Khoussainov
Descriptional Complexity of Determinization and Complementation for Finite Automata. CATS (2011)