Nan Rosemary Ke

Nan Rosemary Ke

École Polytechnique de Montréal

H-index: 25

North America-Canada

About Nan Rosemary Ke

Nan Rosemary Ke, With an exceptional h-index of 25 and a recent h-index of 23 (since 2020), a distinguished researcher at École Polytechnique de Montréal, specializes in the field of Deep Learning, Causal Modeling, Sequence Modeling, Machine Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Scaling instructable agents across many simulated worlds

Neural Causal Structure Discovery from Interventions

Discogen: Learning to discover gene regulatory networks

Learning how to infer partial mdps for in-context adaptation and exploration

Learning to induce causal structure

Learning causal overhypotheses through exploration in children and computational models

Retrieval-augmented reinforcement learning

Towards understanding how machines can learn causal overhypotheses

Nan Rosemary Ke Information

University

Position

PhD student MILA University of Montreal

Citations(all)

3636

Citations(since 2020)

3262

Cited By

1186

hIndex(all)

25

hIndex(since 2020)

23

i10Index(all)

31

i10Index(since 2020)

31

Email

University Profile Page

École Polytechnique de Montréal

Google Scholar

View Google Scholar Profile

Nan Rosemary Ke Skills & Research Interests

Deep Learning

Causal Modeling

Sequence Modeling

Machine Learning

Top articles of Nan Rosemary Ke

Title

Journal

Author(s)

Publication Date

Scaling instructable agents across many simulated worlds

arXiv preprint arXiv:2404.10179

Maria Abi Raad

Arun Ahuja

Catarina Barros

Frederic Besse

Andrew Bolt

...

2024/3/13

Neural Causal Structure Discovery from Interventions

Transactions on Machine Learning Research

Nan Rosemary Ke

Olexa Bilaniuk

Anirudh Goyal

Stefan Bauer

Hugo Larochelle

...

2023/4/15

Discogen: Learning to discover gene regulatory networks

arXiv preprint arXiv:2304.05823

Nan Rosemary Ke

Sara-Jane Dunn

Jorg Bornschein

Silvia Chiappa

Melanie Rey

...

2023/4/12

Learning how to infer partial mdps for in-context adaptation and exploration

arXiv preprint arXiv:2302.04250

Chentian Jiang

Nan Rosemary Ke

Hado van Hasselt

2023/2/8

Learning to induce causal structure

arXiv preprint arXiv:2204.04875

Nan Rosemary Ke

Silvia Chiappa

Jane Wang

Anirudh Goyal

Jorg Bornschein

...

2022/4/11

Learning causal overhypotheses through exploration in children and computational models

Eliza Kosoy

Adrian Liu

Jasmine L Collins

David Chan

Jessica B Hamrick

...

2022/6/28

Retrieval-augmented reinforcement learning

Anirudh Goyal

Abram Friesen

Andrea Banino

Theophane Weber

Nan Rosemary Ke

...

2022/6/28

Towards understanding how machines can learn causal overhypotheses

arXiv preprint arXiv:2206.08353

Eliza Kosoy

David M Chan

Adrian Liu

Jasmine Collins

Bryanna Kaufmann

...

2022/6/16

On the generalization and adaption performance of causal models

arXiv preprint arXiv:2206.04620

Nino Scherrer

Anirudh Goyal

Stefan Bauer

Yoshua Bengio

Nan Rosemary Ke

2022/6/9

Temporal latent bottleneck: Synthesis of fast and slow processing mechanisms in sequence learning

arXiv preprint arXiv:2205.14794

Aniket Didolkar

Kshitij Gupta

Anirudh Goyal

Nitesh B. Gundavarapu

Alex Lamb

...

2022/5/30

On the convergence of continuous constrained optimization for structure learning

Ignavier Ng

Sébastien Lachapelle

Nan Rosemary Ke

Simon Lacoste-Julien

Kun Zhang

2022/5/3

Learning latent structural causal models

arXiv preprint arXiv:2210.13583

Jithendaraa Subramanian

Yashas Annadani

Ivaxi Sheth

Nan Rosemary Ke

Tristan Deleu

...

2022/10/24

Toward causal representation learning

Proceedings of the IEEE

Bernhard Schölkopf

Francesco Locatello

Stefan Bauer

Nan Rosemary Ke

Nal Kalchbrenner

...

2021/2/26

Neural production systems

Advances in Neural Information Processing Systems

Anirudh Goyal ALIAS PARTH GOYAL

Aniket Didolkar

Nan Rosemary Ke

Charles Blundell

Philippe Beaudoin

...

2021/12/6

Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning

arXiv preprint arXiv:2107.00848

Nan Rosemary Ke

Aniket Didolkar

Sarthak Mittal

Anirudh Goyal

Guillaume Lajoie

...

2021/7/2

Learning neural causal models with active interventions

arXiv preprint arXiv:2109.02429

Nino Scherrer

Olexa Bilaniuk

Yashas Annadani

Anirudh Goyal

Patrick Schwab

...

2021/9/6

Prequential MDL for causal structure learning with neural networks

arXiv preprint arXiv:2107.05481

Jorg Bornschein

Silvia Chiappa

Alan Malek

Rosemary Nan Ke

2021/7/2

Fast and slow learning of recurrent independent mechanisms

arXiv preprint arXiv:2105.08710

Kanika Madan

Nan Rosemary Ke

Anirudh Goyal

Bernhard Schölkopf

Yoshua Bengio

2021/5/18

Coordination among neural modules through a shared global workspace

Anirudh Goyal

Aniket Didolkar

Alex Lamb

Kartikeya Badola

Nan Rosemary Ke

...

2022/3

Amortized learning of neural causal representations

arXiv preprint arXiv:2008.09301

Nan Rosemary Ke

Jane Wang

Jovana Mitrovic

Martin Szummer

Danilo J Rezende

2020/8/21

See List of Professors in Nan Rosemary Ke University(École Polytechnique de Montréal)

Co-Authors

H-index: 227
Yoshua Bengio

Yoshua Bengio

Université de Montréal

H-index: 98
Aaron Courville

Aaron Courville

Université de Montréal

H-index: 74
Joelle Pineau

Joelle Pineau

McGill University

H-index: 70
Michael Mozer

Michael Mozer

University of Colorado Boulder

H-index: 31
Anirudh Goyal

Anirudh Goyal

Université de Montréal

H-index: 10
Olexa Bilaniuk

Olexa Bilaniuk

Université de Montréal

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