TA4b: Advances in Causal Inference - Theory and Applications
Tue, 28 Oct, 10:15 - 11:55 PT (UTC -8)
Location: Nautilus
Session Type: Lecture
Session Co-Chairs: Petar Djurić, Stony Brook University and Daniel Waxman, Stony Brook University
Track: Adaptive Systems, Machine Learning, and Data Analytics
Tue, 28 Oct, 10:15 - 10:40 PT (UTC -8)

TA4b.1: Non-negative DAG Learning from Time-Series Data
Samuel Rey, King Juan Carlos University, Spain; Gonzalo Mateos, University of Rochester, United States
Tue, 28 Oct, 10:40 - 11:05 PT (UTC -8)

TA4b.2: Subgraph-Based Causal Discovery under Non-Linear Models and Soft Interventions
Chen Peng, Urbashi Mitra, University of Southern California, United States
Tue, 28 Oct, 11:05 - 11:30 PT (UTC -8)

TA4b.3: Rethinking Chronological Causal Discovery with Signal Processing
Kurt Butler, Damian Machlanski, Panagiotis Dimitrakopoulos, Sotirios Tsaftaris, University of Edinburgh, United Kingdom
Tue, 28 Oct, 11:30 - 11:55 PT (UTC -8)

TA4b.4: Non-Stationary Causal Learning via Hierarchical Modeling
Daniel Waxman, Petar Djuric, Stony Brook University, United States