2024
Learning Signals and Graphs from Time-Series Graph Data with Few Causes
ICASSP 2024accepted
In this paper we port assumptions and techniques from DAG (directed acyclic graph) learning and causal inference to time-series graph data. In particular, we view such data as indexed by a DAG obtained by unrolling the graph in time and generated by a causal linear structural equation model (SEM) fr…