From Ordinary Differential Equations to Structural Causal Models: the
deterministic case

From Ordinary Differential Equations to Structural Causal Models: the deterministic case

9 August 2014

Joris Mooij

Dominik Janzing

Bernhard Schölkopf

Papers citing "From Ordinary Differential Equations to Structural Causal Models: the deterministic case"

19 / 19 papers shown

Title
Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes Georg Manten Cecilia Casolo E. Ferrucci Søren Wengel Mogensen C. Salvi Niki Kilbertus CML BDL 44 8 0 28 Feb 2024
Discovering Causal Relations and Equations from Data Gustau Camps-Valls Andreas Gerhardus Urmi Ninad Gherardo Varando Georg Martius E. Balaguer-Ballester Ricardo Vinuesa Emiliano Díaz L. Zanna Jakob Runge PINN AI4Cl AI4CE CML 35 72 0 21 May 2023
A Causal Research Pipeline and Tutorial for Psychologists and Social Scientists M. Vowels CML 32 2 0 10 Jun 2022
Amortized Inference for Causal Structure Learning Lars Lorch Scott Sussex Jonas Rothfuss Andreas Krause Bernhard Schölkopf CML 26 60 0 25 May 2022
From Statistical to Causal Learning Bernhard Schölkopf Julius von Kügelgen CML 28 45 0 01 Apr 2022
Diffusion Causal Models for Counterfactual Estimation Pedro Sanchez Sotirios A. Tsaftaris DiffM BDL 19 68 0 21 Feb 2022
Learning soft interventions in complex equilibrium systems M. Besserve Bernhard Schölkopf 16 3 0 10 Dec 2021
Causal Multi-Agent Reinforcement Learning: Review and Open Problems St John Grimbly Jonathan P. Shock Arnu Pretorius 44 17 0 12 Nov 2021
Beyond Predictions in Neural ODEs: Identification and Interventions H. Aliee Fabian J. Theis Niki Kilbertus CML 20 24 0 23 Jun 2021
Causal Navigation by Continuous-time Neural Networks Charles J. Vorbach Ramin Hasani Alexander Amini Mathias Lechner Daniela Rus 21 47 0 15 Jun 2021
Neural graphical modelling in continuous-time: consistency guarantees and algorithms Alexis Bellot K. Branson M. Schaar CML AI4TS 17 43 0 06 May 2021
Normalized multivariate time series causality analysis and causal graph reconstruction X. Liang CML AI4TS 25 58 0 23 Apr 2021
D'ya like DAGs? A Survey on Structure Learning and Causal Discovery M. Vowels Necati Cihan Camgöz Richard Bowden CML 37 296 0 03 Mar 2021
Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-values S. Weichwald M. E. Jakobsen Phillip B. Mogensen Lasse Petersen Nikolaj Thams Gherardo Varando CML AI4TS 13 25 0 21 Feb 2020
What can be estimated? Identifiability, estimability, causal inference and ill-posed inverse problems Oliver J. Maclaren R. Nicholson 15 32 0 04 Apr 2019
Structural causal models for macro-variables in time-series Dominik Janzing Paul Kishan Rubenstein Bernhard Schölkopf CML 13 6 0 11 Apr 2018
Causal Consistency of Structural Equation Models Paul Kishan Rubenstein S. Weichwald Stephan Bongers Joris M. Mooij Dominik Janzing Moritz Grosse-Wentrup Bernhard Schölkopf CML 14 122 0 04 Jul 2017
From Deterministic ODEs to Dynamic Structural Causal Models Paul Kishan Rubenstein Stephan Bongers Bernhard Schölkopf Joris M. Mooij 21 52 0 29 Aug 2016
A Discovery Algorithm for Directed Cyclic Graphs Thomas S. Richardson CML 78 193 0 13 Feb 2013