Thomas Lee

About

Hi! I am a PhD student, supervised by Amos Storkey, in the school of Informatics at Edinburgh University and I am part of the Bayesian and Neural Systems group. My primary interests are in machine learning, and I currently focus on designing and analysing systems which learn to perform tasks given an online stream of data. Prior to the PhD, I completed a master’s and bachelor’s in Computer Science at the University of Cambridge.

Publications

For a full list of pulications check out my google scholar page.

Lightweight Online Adaption for Time Series Foundation Model Forecasts [paper]
T. L. Lee*, W. Toner*, R. Singh, A. Joosem, and M. Asenov. Pre-print, 2025.

Performance of Zero-Shot Time Series Foundation Models on Cloud Data [paper]
W. Toner*, T. L. Lee*, A. Joosem, R. Singh, and M. Asenov. ICLR, I Can’t Believe It’s Not Better Workshop, 2025.

Chunking: Continual Learning is not just about Distribution Shift [paper]
T. L. Lee, and A. Storkey. CoLLAs, 2024. (Oral)

Approximate Bayesian Class-Conditional Models under Continuous Representation Shift [paper]
T. L. Lee, and A. Storkey. AISTATS, 2024.

Hyperparameter Selection in Continual Learning [paper]
T. L. Lee, S. P. Hellan, L. Ericsson, E. J. Crowley, and A. Storkey. CoLLAs Workshop, 2024.

On Overcompression in Continual Semantic Segmentation [paper]
M. Kowalski, T. L. Lee, and A. Storkey. Pre-print, 2022.