Hello there! I'm a research scientist at DeepMind, where I work on reinforcement learning and representation learning.
In my spare time, I blog about things that interest me.
I've put some recent papers below. A full list of my publications can be found here.
Learning Dynamics and Generalization in Reinforcement Learning. Clare Lyle, Mark Rowland, Will Dabney, Marta Kwiatkowska, Yarin Gal. ICML 2022, RLDM Spotlight. (arXiv link).
Revisiting the train loss: an efficient performance estimator for neural architecture search. Binxin Ru*, Clare Lyle*, Lisa Schut, Mark van der Wilk, and Yarin Gal. NeurIPS 2021. (arXiv link).
On The Effect of Auxiliary Tasks on Representation Dynamics Clare Lyle*, Mark Rowland*, Georg Ostrovski, Will Dabney, AISTATS 2021. (arXiv link).
I've given a few talks during my PhD. Most of these weren't recorded, but the slides might still be useful to give a narrative overview of some of the projects I've worked on.
Simons Institute Workshop on Theory of Deep RL, October 2020. Invariant Prediction for Generalization in RL | Talk recording | Slides
GenU Workshop, October 2021. Bayesian Model Selection and Generalization in Deep Learning | Slides
G-Research ML College, November 2021. The Many Faces of Model Selection | Slides
OxCSML Group, December 2021. Representation Dynamics and Feature Collapse in RL | Slides
Warning! This blog is not optimized for mobile devices and contains a lot of long equations that will be a pain to view on your phone. Unless you enjoy suffering, I strongly recommend reading it on large screens only.