2 papers
cs.LG2024
MotifDisco: Motif Causal Discovery For Time Series Motifs
Josephine Lamp, Mark Derdzinski, Christopher Hannemann +2
Many time series, particularly health data streams, can be best understood as a sequence of phenomenon or events, which we call \textit{motifs}. A time series motif is a short trac…
cs.LG2023
GlucoSynth: Generating Differentially-Private Synthetic Glucose Traces
Josephine Lamp, Mark Derdzinski, Christopher Hannemann +4
We focus on the problem of generating high-quality, private synthetic glucose traces, a task generalizable to many other time series sources. Existing methods for time series data…