2 papers
cs.LG2026
Adapting Time Series Foundation Models through Data Mixtures
Thomas L. Lee, Edoardo M. Ponti, Amos Storkey
Time series foundation models (TSFMs) have become increasingly popular for zero-shot forecasting. However, for a new time series domain not fully covered by the pretraining set, pe…
cs.LG2026
Signature-Kernel Based Evaluation Metrics for Robust Probabilistic and Tail-Event Forecasting
Benjamin R. Redhead, Thomas L. Lee, Peng Gu +2
Probabilistic forecasting is increasingly critical across high-stakes domains, from finance and epidemiology to climate science. However, current evaluation frameworks lack a conse…