2 citations · 2 across the 1 of their papers we have counts for
2 papers
stat.ML2020
DYNOTEARS: Structure Learning from Time-Series Data
Roxana Pamfil, Nisara Sriwattanaworachai, Shaan Desai +4
We revisit the structure learning problem for dynamic Bayesian networks and propose a method that simultaneously estimates contemporaneous (intra-slice) and time-lagged (inter-slic…
cs.AI2017★ 2 cited
Constrained Bayesian Networks: Theory, Optimization, and Applications
Paul Beaumont, Michael Huth
We develop the theory and practice of an approach to modelling and probabilistic inference in causal networks that is suitable when application-specific or analysis-specific constr…