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20232026
most citedSignature-Kernel Based Evaluation Metrics for Robust Probabilistic and Tail-Event Forecasting

1 citations · 1 across the 6 of their papers we have counts for

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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★ 1 cited

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…