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ORCIDClare Lyle
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2020 – today
- 2022
[i17]Clare Lyle, Mark Rowland, Will Dabney:
Understanding and Preventing Capacity Loss in Reinforcement Learning. CoRR abs/2204.09560 (2022)- 2021
- [c9]Clare Lyle, Mark Rowland, Georg Ostrovski, Will Dabney:
On the Effect of Auxiliary Tasks on Representation Dynamics. AISTATS 2021: 1-9 - [c8]Angelos Filos, Clare Lyle, Yarin Gal, Sergey Levine, Natasha Jaques, Gregory Farquhar:
PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning. ICML 2021: 3305-3317 - [c7]Benjie Wang, Clare Lyle, Marta Kwiatkowska:
Provable Guarantees on the Robustness of Decision Rules to Causal Interventions. IJCAI 2021: 4258-4265 - [c6]Robin Ru, Clare Lyle, Lisa Schut, Miroslav Fil, Mark van der Wilk, Yarin Gal:
Speedy Performance Estimation for Neural Architecture Search. NeurIPS 2021: 4079-4092 - [c5]Jannik Kossen, Neil Band, Clare Lyle, Aidan N. Gomez, Thomas Rainforth, Yarin Gal:
Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning. NeurIPS 2021: 28742-28756 - [i16]Angelos Filos, Clare Lyle, Yarin Gal, Sergey Levine, Natasha Jaques, Gregory Farquhar:
PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning. CoRR abs/2102.12560 (2021) - [i15]Clare Lyle, Mark Rowland, Georg Ostrovski, Will Dabney:
On The Effect of Auxiliary Tasks on Representation Dynamics. CoRR abs/2102.13089 (2021) - [i14]Lorenz Kuhn, Clare Lyle, Aidan N. Gomez, Jonas Rothfuss, Yarin Gal:
Robustness to Pruning Predicts Generalization in Deep Neural Networks. CoRR abs/2103.06002 (2021) - [i13]Benjie Wang, Clare Lyle, Marta Kwiatkowska:
Provable Guarantees on the Robustness of Decision Rules to Causal Interventions. CoRR abs/2105.09108 (2021) - [i12]Jannik Kossen, Neil Band, Clare Lyle, Aidan N. Gomez, Tom Rainforth, Yarin Gal:
Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning. CoRR abs/2106.02584 (2021) - [i11]Miroslav Fil, Binxin Ru, Clare Lyle, Yarin Gal:
DARTS without a Validation Set: Optimizing the Marginal Likelihood. CoRR abs/2112.13023 (2021) - 2020
- [c4]Amy Zhang, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup:
Invariant Causal Prediction for Block MDPs. ICML 2020: 11214-11224 - [c3]Clare Lyle, Lisa Schut, Robin Ru, Yarin Gal, Mark van der Wilk:
A Bayesian Perspective on Training Speed and Model Selection. NeurIPS 2020 - [i10]Amy Zhang
, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup:
Invariant Causal Prediction for Block MDPs. CoRR abs/2003.06016 (2020) - [i9]Andreas Kirsch, Clare Lyle, Yarin Gal:
Unpacking Information Bottlenecks: Unifying Information-Theoretic Objectives in Deep Learning. CoRR abs/2003.12537 (2020) - [i8]Clare Lyle, Mark van der Wilk, Marta Kwiatkowska, Yarin Gal, Benjamin Bloem-Reddy:
On the Benefits of Invariance in Neural Networks. CoRR abs/2005.00178 (2020) - [i7]Binxin Ru, Clare Lyle, Lisa Schut, Mark van der Wilk, Yarin Gal:
Revisiting the Train Loss: an Efficient Performance Estimator for Neural Architecture Search. CoRR abs/2006.04492 (2020) - [i6]Clare Lyle, Lisa Schut, Binxin Ru, Yarin Gal, Mark van der Wilk:
A Bayesian Perspective on Training Speed and Model Selection. CoRR abs/2010.14499 (2020)
2010 – 2019
- 2019
- [c2]Clare Lyle, Marc G. Bellemare, Pablo Samuel Castro:
A Comparative Analysis of Expected and Distributional Reinforcement Learning. AAAI 2019: 4504-4511 - [c1]Marc G. Bellemare, Will Dabney, Robert Dadashi, Adrien Ali Taïga, Pablo Samuel Castro, Nicolas Le Roux, Dale Schuurmans, Tor Lattimore, Clare Lyle:
A Geometric Perspective on Optimal Representations for Reinforcement Learning. NeurIPS 2019: 4360-4371 - [i5]Clare Lyle, Pablo Samuel Castro, Marc G. Bellemare:
A Comparative Analysis of Expected and Distributional Reinforcement Learning. CoRR abs/1901.11084 (2019) - [i4]Marc G. Bellemare, Will Dabney, Robert Dadashi, Adrien Ali Taïga, Pablo Samuel Castro, Nicolas Le Roux, Dale Schuurmans, Tor Lattimore, Clare Lyle:
A Geometric Perspective on Optimal Representations for Reinforcement Learning. CoRR abs/1901.11530 (2019) - 2018
- [i3]Miles Brundage, Shahar Avin, Jack Clark, Helen Toner, Peter Eckersley, Ben Garfinkel, Allan Dafoe, Paul Scharre, Thomas Zeitzoff, Bobby Filar, Hyrum S. Anderson, Heather Roff, Gregory C. Allen, Jacob Steinhardt, Carrick Flynn, Seán Ó hÉigeartaigh, Simon Beard, Haydn Belfield, Sebastian Farquhar, Clare Lyle, Rebecca Crootof, Owain Evans, Michael Page, Joanna Bryson, Roman Yampolskiy, Dario Amodei:
The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation. CoRR abs/1802.07228 (2018) - [i2]Thang Doan, Bogdan Mazoure, Clare Lyle:
GAN Q-learning. CoRR abs/1805.04874 (2018) - 2016
- [i1]Cody Barnson, Dawn Chandler, Qiao Chen, Christina Chung, Andrew Coccimiglio, Sean La, Lily Li, Aïna Linn, Anna Lubiw, Clare Lyle, Shikha Mahajan, Gregory W. Mierzwinski, Simon Pratt, Yoon Su Yoo, Hongbo Zhang, Kevin Zhang:
Some Counterexamples for Compatible Triangulations. CoRR abs/1612.04861 (2016)
Coauthor Index
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