BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery

BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery

6 December 2021

Papers citing "BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery"

11 / 11 papers shown

Title
Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders Christian Toth Christian Knoll Franz Pernkopf Robert Peharz CML 35 1 0 22 Feb 2024
Order-based Structure Learning with Normalizing Flows Hamidreza Kamkari Vahid Balazadeh Meresht Vahid Zehtab Rahul G. Krishnan CML 12 1 0 14 Aug 2023
Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation Chris C. Emezue Alexandre Drouin T. Deleu Stefan Bauer Yoshua Bengio CML 8 2 0 11 Jul 2023
Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network T. Deleu Mizu Nishikawa-Toomey Jithendaraa Subramanian Nikolay Malkin Laurent Charlin Yoshua Bengio BDL 10 43 0 30 May 2023
CUTS+: High-dimensional Causal Discovery from Irregular Time-series Yuxiao Cheng Lianglong Li Tingxiong Xiao Zongren Li Qionghai Dai J. Suo K. He CML BDL AI4TS 8 21 0 10 May 2023
A theory of continuous generative flow networks Salem Lahlou T. Deleu Pablo Lemos Dinghuai Zhang Alexandra Volokhova Alex Hernández-García Léna Néhale Ezzine Yoshua Bengio Nikolay Malkin AI4CE 8 79 0 30 Jan 2023
DAG Learning on the Permutahedron Valentina Zantedeschi Luca Franceschi Jean Kaddour Matt J. Kusner Vlad Niculae 14 11 0 27 Jan 2023
$Trust Your $\nabla$: Gradient-based Intervention Targeting for Causal Discovery$ Trust Your $\nabla$ : Gradient-based Intervention Targeting for Causal Discovery Mateusz Olko Michal Zajac A. Nowak Nino Scherrer Yashas Annadani Stefan Bauer Lukasz Kucinski Piotr Milos CML 14 2 0 24 Nov 2022
BaCaDI: Bayesian Causal Discovery with Unknown Interventions Alexander Hagele Jonas Rothfuss Lars Lorch Vignesh Ram Somnath Bernhard Schölkopf Andreas Krause CML BDL 23 19 0 03 Jun 2022
Interventions, Where and How? Experimental Design for Causal Models at Scale P. Tigas Yashas Annadani Andrew Jesson Bernhard Schölkopf Y. Gal Stefan Bauer CML 18 48 0 03 Mar 2022
DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks Dennis L. Wei Tian Gao Yue Yu CML 48 71 0 18 Oct 2020