Detecting non-causal artifacts in multivariate linear regression models

2 March 2018

Papers citing "Detecting non-causal artifacts in multivariate linear regression models"

13 / 13 papers shown

Title
Pearl Causal Hierarchy on Image Data: Intricacies & Challenges Matej Zečević Moritz Willig Devendra Singh Dhami Kristian Kersting 51 2 0 23 Dec 2022
From Statistical to Causal Learning Bernhard Schölkopf Julius von Kügelgen CML 100 46 0 01 Apr 2022
Interpolation and Regularization for Causal Learning L. C. Vankadara Luca Rendsburg U. V. Luxburg Debarghya Ghoshdastidar CML 50 1 0 18 Feb 2022
Correcting Confounding via Random Selection of Background Variables You-Lin Chen Lenon Minorics Dominik Janzing CML 59 4 0 04 Feb 2022
Optimal transport for causal discovery Ruibo Tu Kun Zhang Hedvig Kjellström Cheng Zhang 137 20 0 23 Jan 2022
Deconfounded Score Method: Scoring DAGs with Dense Unobserved Confounding Alexis Bellot M. Schaar CML 75 11 0 28 Mar 2021
Towards Causal Representation Learning Bernhard Schölkopf Francesco Locatello Stefan Bauer Nan Rosemary Ke Nal Kalchbrenner Anirudh Goyal Yoshua Bengio OOD CML AI4CE 155 322 0 22 Feb 2021
Causality for Machine Learning Bernhard Schölkopf CML AI4CE LRM 109 465 0 24 Nov 2019
Leveraging directed causal discovery to detect latent common causes Ciarán M. Gilligan-Lee Chris Hart Jonathan G. Richens Saurabh Johri CML 92 16 0 22 Oct 2019
Causal Regularization M. T. Bahadori OOD CML 97 51 0 28 Jun 2019
Semi-Supervised Learning, Causality and the Conditional Cluster Assumption Julius von Kügelgen A. Mey Marco Loog Bernhard Schölkopf CML 69 26 0 28 May 2019
We Are Not Your Real Parents: Telling Causal from Confounded using MDL David Kaltenpoth Jilles Vreeken CML 114 22 0 21 Jan 2019
The Blessings of Multiple Causes Yixin Wang David M. Blei AI4CE CML 70 291 0 17 May 2018