Nan Rosemary Ke

According to our database, Nan Rosemary Ke authored at least 56 papers between 2011 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

AI-Assisted Generation of Difficult Math Questions.

Vedant Shah, Dingli Yu, Kaifeng Lyu, Simon Park, Nan Rosemary Ke, Michael Mozer, Yoshua Bengio, Sanjeev Arora, Anirudh Goyal

CoRR, 2024

Learning Beyond Pattern Matching? Assaying Mathematical Understanding in LLMs.

Siyuan Guo, Aniket Didolkar, Nan Rosemary Ke, Anirudh Goyal, Ferenc Huszár, Bernhard Schölkopf

CoRR, 2024

Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving.

Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Siyuan Guo, Michal Valko, Timothy P. Lillicrap, Danilo J. Rezende, Yoshua Bengio, Michael Mozer, Sanjeev Arora

CoRR, 2024

Scaling Instructable Agents Across Many Simulated Worlds.

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

CoRR, 2024

2023

Neural Causal Structure Discovery from Interventions.

Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Bernhard Schölkopf, Michael Curtis Mozer, Christopher Pal, Yoshua Bengio

Trans. Mach. Learn. Res., 2023

DiscoGen: Learning to Discover Gene Regulatory Networks.

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

CoRR, 2023

Learning How to Infer Partial MDPs for In-Context Adaptation and Exploration.

Chentian Jiang, Nan Rosemary Ke, Hado van Hasselt

CoRR, 2023

Learning to Induce Causal Structure.

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

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Towards Understanding How Machines Can Learn Causal Overhypotheses.

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

Proceedings of the 45th Annual Meeting of the Cognitive Science Society, 2023

2022

Learning Latent Structural Causal Models.

Jithendaraa Subramanian, Yashas Annadani, Ivaxi Sheth, Nan Rosemary Ke, Tristan Deleu, Stefan Bauer, Derek Nowrouzezahrai, Samira Ebrahimi Kahou

CoRR, 2022

Towards Understanding How Machines Can Learn Causal Overhypotheses.

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

CoRR, 2022

On the Generalization and Adaption Performance of Causal Models.

Nino Scherrer, Anirudh Goyal, Stefan Bauer, Yoshua Bengio, Nan Rosemary Ke

CoRR, 2022

Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning.

Aniket Didolkar, Kshitij Gupta, Anirudh Goyal, Alex Lamb, Nan Rosemary Ke, Yoshua Bengio

CoRR, 2022

Learning to Induce Causal Structure.

Nan Rosemary Ke, Silvia Chiappa, Jane Wang, Jörg Bornschein, Theophane Weber, Anirudh Goyal, Matthew M. Botvinick, Michael Mozer, Danilo Jimenez Rezende

CoRR, 2022

Retrieval-Augmented Reinforcement Learning.

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

CoRR, 2022

Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning.

Aniket Didolkar, Kshitij Gupta, Anirudh Goyal, Nitesh B. Gundavarapu, Alex Lamb, Nan Rosemary Ke, Yoshua Bengio

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Retrieval-Augmented Reinforcement Learning.

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

Proceedings of the International Conference on Machine Learning, 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

Proceedings of the Tenth International Conference on Learning Representations, 2022

Learning Causal Overhypotheses through Exploration in Children and Computational Models.

Eliza Kosoy, Adrian Liu, Jasmine Collins, David M. Chan, Jessica B. Hamrick, Sandy Han Huang, Nan Rosemary Ke, Bryanna Kaufmann, Alison Gopnik

Proceedings of the 44th Annual Meeting of the Cognitive Science Society, 2022

Learning Causal Overhypotheses through Exploration in Children and Computational Models.

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

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

On the Convergence of Continuous Constrained Optimization for Structure Learning.

Ignavier Ng, Sébastien Lachapelle, Nan Rosemary Ke, Simon Lacoste-Julien, Kun Zhang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Toward Causal Representation Learning.

Bernhard Schölkopf, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke, Nal Kalchbrenner, Anirudh Goyal, Yoshua Bengio

Proc. IEEE, 2021

Learning Neural Causal Models with Active Interventions.

Nino Scherrer, Olexa Bilaniuk, Yashas Annadani, Anirudh Goyal, Patrick Schwab, Bernhard Schölkopf, Michael C. Mozer, Yoshua Bengio, Stefan Bauer, Nan Rosemary Ke

CoRR, 2021

Prequential MDL for Causal Structure Learning with Neural Networks.

Jörg Bornschein, Silvia Chiappa, Alan Malek, Nan Rosemary Ke

CoRR, 2021

Towards Causal Representation Learning.

Bernhard Schölkopf, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke, Nal Kalchbrenner, Anirudh Goyal, Yoshua Bengio

CoRR, 2021

Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning.

Nan Rosemary Ke, Aniket Didolkar, Sarthak Mittal, Anirudh Goyal, Guillaume Lajoie, Stefan Bauer, Danilo Jimenez Rezende, Michael Mozer, Yoshua Bengio, Chris Pal

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Neural Production Systems.

Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Charles Blundell, Philippe Beaudoin, Nicolas Heess, Michael Mozer, Yoshua Bengio

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Fast And Slow Learning Of Recurrent Independent Mechanisms.

Kanika Madan, Nan Rosemary Ke, Anirudh Goyal, Bernhard Schölkopf, Yoshua Bengio

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

On the Convergence of Continuous Constrained Optimization for Structure Learning.

Ignavier Ng, Sébastien Lachapelle, Nan Rosemary Ke, Simon Lacoste-Julien

CoRR, 2020

Amortized learning of neural causal representations.

Nan Rosemary Ke, Jane X. Wang, Jovana Mitrovic, Martin Szummer, Danilo J. Rezende

CoRR, 2020

Causally Correct Partial Models for Reinforcement Learning.

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

CoRR, 2020

A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms.

Yoshua Bengio, Tristan Deleu, Nasim Rahaman, Nan Rosemary Ke, Sébastien Lachapelle, Olexa Bilaniuk, Anirudh Goyal, Christopher J. Pal

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Learning Neural Causal Models from Unknown Interventions.

Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Chris Pal, Yoshua Bengio

CoRR, 2019

Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future.

Nan Rosemary Ke, Amanpreet Singh, Ahmed Touati, Anirudh Goyal, Yoshua Bengio, Devi Parikh, Dhruv Batra

CoRR, 2019

Modeling the Long Term Future in Model-Based Reinforcement Learning.

Nan Rosemary Ke, Amanpreet Singh, Ahmed Touati, Anirudh Goyal, Yoshua Bengio, Devi Parikh, Dhruv Batra

Proceedings of the 7th International Conference on Learning Representations, 2019

h-detach: Modifying the LSTM Gradient Towards Better Optimization.

Bhargav Kanuparthi, Devansh Arpit, Giancarlo Kerg, Nan Rosemary Ke, Ioannis Mitliagkas, Yoshua Bengio

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Adversarial Gain.

Peter Henderson, Koustuv Sinha, Nan Rosemary Ke, Joelle Pineau

CoRR, 2018

Sparse Attentive Backtracking: Temporal CreditAssignment Through Reminding.

Nan Rosemary Ke, Anirudh Goyal, Olexa Bilaniuk, Jonathan Binas, Michael C. Mozer, Chris Pal, Yoshua Bengio

CoRR, 2018

A Deep Reinforcement Learning Chatbot (Short Version).

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

CoRR, 2018

Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding.

Nan Rosemary Ke, Anirudh Goyal, Olexa Bilaniuk, Jonathan Binas, Michael C. Mozer, Chris Pal, Yoshua Bengio

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Focused Hierarchical RNNs for Conditional Sequence Processing.

Nan Rosemary Ke, Konrad Zolna, Alessandro Sordoni, Zhouhan Lin, Adam Trischler, Yoshua Bengio, Joelle Pineau, Laurent Charlin, Christopher J. Pal

Proceedings of the 35th International Conference on Machine Learning, 2018

Twin Networks: Matching the Future for Sequence Generation.

Dmitriy Serdyuk, Nan Rosemary Ke, Alessandro Sordoni, Adam Trischler, Chris Pal, Yoshua Bengio

Proceedings of the 6th International Conference on Learning Representations, 2018

Ethical Challenges in Data-Driven Dialogue Systems.

Peter Henderson, Koustuv Sinha, Nicolas Angelard-Gontier, Nan Rosemary Ke, Genevieve Fried, Ryan Lowe, Joelle Pineau

Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society, 2018

2017

ACtuAL: Actor-Critic Under Adversarial Learning.

Anirudh Goyal, Nan Rosemary Ke, Alex Lamb, R. Devon Hjelm, Chris Pal, Joelle Pineau, Yoshua Bengio

CoRR, 2017

Sparse Attentive Backtracking: Long-Range Credit Assignment in Recurrent Networks.

Nan Rosemary Ke, Anirudh Goyal, Olexa Bilaniuk, Jonathan Binas, Laurent Charlin, Chris Pal, Yoshua Bengio

CoRR, 2017

A Deep Reinforcement Learning Chatbot.

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

CoRR, 2017

Twin Networks: Using the Future as a Regularizer.

Dmitriy Serdyuk, Nan Rosemary Ke, Alessandro Sordoni, Chris Pal, Yoshua Bengio

CoRR, 2017

Z-Forcing: Training Stochastic Recurrent Networks.

Anirudh Goyal, Alessandro Sordoni, Marc-Alexandre Côté, Nan Rosemary Ke, Yoshua Bengio

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net.

Anirudh Goyal, Nan Rosemary Ke, Surya Ganguli, Yoshua Bengio

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations.

David Krueger, Tegan Maharaj, János Kramár, Mohammad Pezeshki, Nicolas Ballas, Nan Rosemary Ke, Anirudh Goyal, Yoshua Bengio, Aaron C. Courville, Christopher J. Pal

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations.

David Krueger, Tegan Maharaj, János Kramár, Mohammad Pezeshki, Nicolas Ballas, Nan Rosemary Ke, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Aaron C. Courville, Chris Pal

CoRR, 2016

Cascading Bandits for Large-Scale Recommendation Problems.

Shi Zong, Hao Ni, Kenny Sung, Nan Rosemary Ke, Zheng Wen, Branislav Kveton

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

2015

Task Loss Estimation for Sequence Prediction.

Dzmitry Bahdanau, Dmitriy Serdyuk, Philemon Brakel, Nan Rosemary Ke, Jan Chorowski, Aaron C. Courville, Yoshua Bengio

CoRR, 2015

Transferring knowledge from a RNN to a DNN.

William Chan, Nan Rosemary Ke, Ian R. Lane

Proceedings of the 16th Annual Conference of the International Speech Communication Association, 2015

2012

Markerless Visual Control of a Quad-Rotor Micro Aerial Vehicle by Means of On-Board Stereo Processing.

Konstantin Schauwecker, Nan Rosemary Ke, Sebastian A. Scherer, Andreas Zell

Proceedings of the Autonomous Mobile Systems 2012, 2012

2011

Descriptional Complexity of Determinization and Complementation for Finite Automata.

Aniruddh Gandhi, Nan Rosemary Ke, Bakhadyr Khoussainov

Proceedings of the Seventeenth Computing: The Australasian Theory Symposium, 2011