Causal Discovery from Soft Interventions with Unknown Targets: Characterization and Learning

By Amin Jaber, Murat Kocaoglu. 2020

131 citations recorded by the source corpus.

Subfields: Causal Inference & Discovery

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Causal Inference & Discovery

1. Alexandre Lacoste
2. Simon Lacoste-Julien
3. Rémi Le Priol
4. Pau Rodr'iguez L'opez
5. Sébastien Lachapelle
6. Richard Bowden
7. Necati Cihan Camgöz
8. Matthew James Vowels

Citations in the corpus

• Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA (2021, background): “…has been explored previously in the context of causal discovery where the intervention occurs on observed variables instead of latent variables like in our case (Eaton and Murphy, 2007; Mooij et al., 2020; Squires et al., 2020; Jaber et al., 2020; Brouillard et al., 2020; Ke et al., 2019).”
• D’ya Like DAGs? A Survey on Structure Learning and Causal Discovery (2021, background): “Other types of graph used to represent causal structure include Partially Oriented Induced Path Graphs (POIPGs) [188, 223], Single World Intervention Graphs (SWIGs) [24, 197, 198], σ-connection graphs [57], undirected graphs [12], interaction and component graphs for dynamic systems [41], Maximal Al”