3 papers
cs.LG2025
Beyond Accuracy: Are Time Series Foundation Models Well-Calibrated?
Coen Adler, Yuxin Chang, Felix Draxler +2
The recent development of foundation models for time series data has generated considerable interest in using such models across a variety of applications. Although foundation mode…
stat.ML2024
Deep Continuous-Time State-Space Models for Marked Event Sequences
Yuxin Chang, Alex Boyd, Cao Xiao +4
Marked temporal point processes (MTPPs) model sequences of events occurring at irregular time intervals, with wide-ranging applications in fields such as healthcare, finance and so…
cs.LG2023
Probabilistic Modeling for Sequences of Sets in Continuous-Time
Yuxin Chang, Alex Boyd, Padhraic Smyth
Neural marked temporal point processes have been a valuable addition to the existing toolbox of statistical parametric models for continuous-time event data. These models are usefu…