Nan Rosemary Ke

According to our database¹, Nan Rosemary Ke authored at least 49 papers between 2011 and 2023.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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In proceedings

Article

PhD thesis

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Links

On csauthors.net:

Bibliography

2023

DiscoGen: Learning to Discover Gene Regulatory Networks.

[BibT_eX]

[DOI]

Jean-Baptiste Lespiau

CoRR, 2023

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

[BibT_eX]

[DOI]

Chentian Jiang

Nan Rosemary Ke

Hado van Hasselt

CoRR, 2023

Learning to Induce Causal Structure.

[BibT_eX]

[DOI]

Danilo Jimenez Rezende

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Learning Latent Structural Causal Models.

[BibT_eX]

[DOI]

Jithendaraa Subramanian

Samira Ebrahimi Kahou

CoRR, 2022

Towards Understanding How Machines Can Learn Causal Overhypotheses.

[BibT_eX]

[DOI]

CoRR, 2022

On the Generalization and Adaption Performance of Causal Models.

[BibT_eX]

[DOI]

CoRR, 2022

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

[BibT_eX]

[DOI]

CoRR, 2022

Learning to Induce Causal Structure.

[BibT_eX]

[DOI]

Danilo Jimenez Rezende

CoRR, 2022

Retrieval-Augmented Reinforcement Learning.

[BibT_eX]

[DOI]

Adrià Puigdomènech Badia

CoRR, 2022

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

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Adrià Puigdomènech Badia

Proceedings of the International Conference on Machine Learning, 2022

Coordination Among Neural Modules Through a Shared Global Workspace.

[BibT_eX]

[DOI]

Anirudh Goyal

Aniket Rajiv Didolkar

Proceedings of the Tenth International Conference on Learning Representations, 2022

Learning Causal Overhypotheses through Exploration in Children and Computational Models.

[BibT_eX]

[DOI]

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

On the Convergence of Continuous Constrained Optimization for Structure Learning.

[BibT_eX]

[DOI]

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

2021

Toward Causal Representation Learning.

[BibT_eX]

[DOI]

Proc. IEEE, 2021

Learning Neural Causal Models with Active Interventions.

[BibT_eX]

[DOI]

CoRR, 2021

Prequential MDL for Causal Structure Learning with Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2021

Towards Causal Representation Learning.

[BibT_eX]

[DOI]

CoRR, 2021

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

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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

2020

On the Convergence of Continuous Constrained Optimization for Structure Learning.

[BibT_eX]

[DOI]

CoRR, 2020

Amortized learning of neural causal representations.

[BibT_eX]

[DOI]

CoRR, 2020

Causally Correct Partial Models for Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2020

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

[BibT_eX]

[DOI]

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

2019

Learning Neural Causal Models from Unknown Interventions.

[BibT_eX]

[DOI]

CoRR, 2019

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

[BibT_eX]

[DOI]

CoRR, 2019

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

[BibT_eX]

[DOI]

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

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

[BibT_eX]

[DOI]

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

2018

Adversarial Gain.

[BibT_eX]

[DOI]

CoRR, 2018

Sparse Attentive Backtracking: Temporal CreditAssignment Through Reminding.

[BibT_eX]

[DOI]

CoRR, 2018

A Deep Reinforcement Learning Chatbot (Short Version).

[BibT_eX]

[DOI]

Alexandre de Brébisson

CoRR, 2018

Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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

Twin Networks: Matching the Future for Sequence Generation.

[BibT_eX]

[DOI]

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

Ethical Challenges in Data-Driven Dialogue Systems.

[BibT_eX]

[DOI]

Peter Henderson

Koustuv Sinha

Nicolas Angelard-Gontier

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

2017

ACtuAL: Actor-Critic Under Adversarial Learning.

[BibT_eX]

[DOI]

CoRR, 2017

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

[BibT_eX]

[DOI]

CoRR, 2017

A Deep Reinforcement Learning Chatbot.

[BibT_eX]

[DOI]

Alexandre de Brébisson

CoRR, 2017

Twin Networks: Using the Future as a Regularizer.

[BibT_eX]

[DOI]

CoRR, 2017

Z-Forcing: Training Stochastic Recurrent Networks.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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

2016

Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations.

[BibT_eX]

[DOI]

CoRR, 2016

Cascading Bandits for Large-Scale Recommendation Problems.

[BibT_eX]

[DOI]

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

2015

Task Loss Estimation for Sequence Prediction.

[BibT_eX]

[DOI]

CoRR, 2015

Transferring knowledge from a RNN to a DNN.

[BibT_eX]

[DOI]

William Chan

Nan Rosemary Ke

Ian R. Lane

Proceedings of the INTERSPEECH 2015, 2015

2012

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

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Aniruddh Gandhi

Nan Rosemary Ke

Bakhadyr Khoussainov

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

Nan Rosemary Ke

Timeline

Legend:

Links

On csauthors.net:

Bibliography

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