Thomas L. Lee

12 papers A* 2A 1Journal 8Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Adapting Time Series Foundation Models through Data Mixtures.
CoRR
Thomas L. Lee, Edoardo M. Ponti, Amos J. Storkey
2026 J jnl
Signature-Kernel Based Evaluation Metrics for Robust Probabilistic and Tail-Event Forecasting.
CoRR
Benjamin R. Redhead, Thomas L. Lee, Peng Gu, Víctor Elvira, Amos J. Storkey
2025 J jnl
Forgetting is Everywhere.
CoRR
Ben Sanati, Thomas L. Lee, Trevor McInroe, Aidan Scannell, Nikolay Malkin, David Abel, Amos Storkey
2025 A* conf
Lightweight Online Adaption for Time Series Foundation Model Forecasts.
ICML
Thomas L. Lee, William Toner, Rajkarn Singh, Artjom Joosen, Martin Asenov
2025 J jnl
Lightweight Online Adaption for Time Series Foundation Model Forecasts.
CoRR
Thomas L. Lee, William Toner, Rajkarn Singh, Artjom Joosem, Martin Asenov
2025 A* conf
Performance of Zero-Shot Time Series Foundation Models on Cloud Data.
ICLR
William Toner, Thomas L. Lee, Artjom Joosen, Rajkarn Singh, Martin Asenov
2025 J jnl
Performance of Zero-Shot Time Series Foundation Models on Cloud Data.
CoRR
William Toner, Thomas L. Lee, Artjom Joosen, Rajkarn Singh, Martin Asenov
2024 A conf
Approximate Bayesian Class-Conditional Models under Continuous Representation Shift.
AISTATS
Thomas L. Lee, Amos J. Storkey
2024 — conf
Chunking: Continual Learning is not just about Distribution Shift.
CoLLAs
Thomas L. Lee, Amos Storkey
2024 J jnl
Hyperparameter Selection in Continual Learning.
CoRR
Thomas L. Lee, Sigrid Passano Hellan, Linus Ericsson, Elliot J. Crowley, Amos Storkey
2023 J jnl
Chunking: Forgetting Matters in Continual Learning even without Changing Tasks.
CoRR
Thomas L. Lee, Amos Storkey
2023 J jnl
Class Conditional Gaussians for Continual Learning.
CoRR
Thomas L. Lee, Amos Storkey