Clare Lyle
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
15
Venues
5
Active years
2019–2025
Best venue rank
A*
Where they publish
Papers
15 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | AISTATS | A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning. | Khimya Khetarpal, Zhaohan Daniel Guo, Bernardo vila Pires, Yunhao Tang, Clare Lyle, Mark Rowland, Nicolas Heess, Diana L. Borsa, Arthur Guez, Will Dabney |
| 2024 | ICML | Slow and Steady Wins the Race: Maintaining Plasticity with Hare and Tortoise Networks. | Hojoon Lee, Hyeonseo Cho, Hyunseung Kim, Donghu Kim, Dugki Min, Jaegul Choo, Clare Lyle |
| 2024 | ICML | Mixtures of Experts Unlock Parameter Scaling for Deep RL. | Johan S. Obando-Ceron, Ghada Sokar, Timon Willi, Clare Lyle, Jesse Farebrother, Jakob Nicolaus Foerster, Gintare Karolina Dziugaite, Doina Precup, Pablo Samuel Castro |
| 2023 | ICML | DiscoBAX: Discovery of optimal intervention sets in genomic experiment design. | Clare Lyle, Arash Mehrjou, Pascal Notin, Andrew Jesson, Stefan Bauer, Yarin Gal, Patrick Schwab |
| 2023 | ICML | Understanding Plasticity in Neural Networks. | Clare Lyle, Zeyu Zheng, Evgenii Nikishin, Bernardo vila Pires, Razvan Pascanu, Will Dabney |
| 2023 | ICML | Quantile Credit Assignment. | Thomas Mesnard, Wenqi Chen, Alaa Saade, Yunhao Tang, Mark Rowland, Theophane Weber, Clare Lyle, Audrunas Gruslys, Michal Valko, Will Dabney, Georg Ostrovski, Eric Moulines, Rmi Munos |
| 2023 | ICML | The Statistical Benefits of Quantile Temporal-Difference Learning for Value Estimation. | Mark Rowland, Yunhao Tang, Clare Lyle, Rmi Munos, Marc G. Bellemare, Will Dabney |
| 2023 | ICML | Understanding Self-Predictive Learning for Reinforcement Learning. | Yunhao Tang, Zhaohan Daniel Guo, Pierre Harvey Richemond, Bernardo vila Pires, Yash Chandak, Rmi Munos, Mark Rowland, Mohammad Gheshlaghi Azar, Charline Le Lan, Clare Lyle, Andrs Gyrgy, Shantanu Thakoor, Will Dabney, Bilal Piot, Daniele Calandriello, Michal Valko |
| 2022 | ICLR | Understanding and Preventing Capacity Loss in Reinforcement Learning. | Clare Lyle, Mark Rowland, Will Dabney |
| 2022 | ICML | Learning Dynamics and Generalization in Deep Reinforcement Learning. | Clare Lyle, Mark Rowland, Will Dabney, Marta Kwiatkowska, Yarin Gal |
| 2021 | AISTATS | On the Effect of Auxiliary Tasks on Representation Dynamics. | Clare Lyle, Mark Rowland, Georg Ostrovski, Will Dabney |
| 2021 | ICML | PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning. | Angelos Filos, Clare Lyle, Yarin Gal, Sergey Levine, Natasha Jaques, Gregory Farquhar |
| 2021 | IJCAI | Provable Guarantees on the Robustness of Decision Rules to Causal Interventions. | Benjie Wang, Clare Lyle, Marta Kwiatkowska |
| 2020 | ICML | Invariant Causal Prediction for Block MDPs. | Amy Zhang, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup |
| 2019 | AAAI | A Comparative Analysis of Expected and Distributional Reinforcement Learning. | Clare Lyle, Marc G. Bellemare, Pablo Samuel Castro |