eCDANs: Efficient Temporal Causal Discovery from Autocorrelated and Non-stationary Data (Student Abstract)

6 March 2023

Papers citing "eCDANs: Efficient Temporal Causal Discovery from Autocorrelated and Non-stationary Data (Student Abstract)"

5 / 5 papers shown

Title
Unsuitability of NOTEARS for Causal Graph Discovery Marcus Kaiser Maksim Sipos CML 96 66 0 12 Apr 2021
Structural Causal Model with Expert Augmented Knowledge to Estimate the Effect of Oxygen Therapy on Mortality in the ICU Md. Osman Gani S. Kethireddy M. Bikak Paul M. Griffin Mohammad Adibuzzaman CML 23 14 0 28 Oct 2020
Discovering contemporaneous and lagged causal relations in autocorrelated nonlinear time series datasets Jakob Runge 69 193 0 07 Mar 2020
DYNOTEARS: Structure Learning from Time-Series Data Roxana Pamfil Nisara Sriwattanaworachai Shaan Desai Philip Pilgerstorfer Paul Beaumont K. Georgatzis Bryon Aragam CML AI4TS BDL 77 192 0 02 Feb 2020
Causal Discovery from Heterogeneous/Nonstationary Data with Independent Changes Erdun Gao Kun Zhang Jiji Zhang Joseph Ramsey Ruben Sanchez-Romero Clark Glymour Bernhard Schölkopf 62 229 0 05 Mar 2019