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"

16 / 16 papers shown

Title
Identifying Causal Direction via Variational Bayesian Compression Quang-Duy Tran Bao Duong Phuoc Nguyen Thin Nguyen CML 24 0 0 12 May 2025
ProDAG: Projection-Induced Variational Inference for Directed Acyclic Graphs Ryan Thompson Edwin V. Bonilla Robert Kohn 31 0 0 24 May 2024
Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders Christian Toth Christian Knoll Franz Pernkopf Robert Peharz CML 43 1 0 22 Feb 2024
Order-based Structure Learning with Normalizing Flows Hamidreza Kamkari Vahid Balazadeh Meresht Vahid Zehtab Rahul G. Krishnan CML 26 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 27 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 30 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 21 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 28 79 0 30 Jan 2023
DAG Learning on the Permutahedron Valentina Zantedeschi Luca Franceschi Jean Kaddour Matt J. Kusner Vlad Niculae 25 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 24 2 0 24 Nov 2022
On the Generalization and Adaption Performance of Causal Models Nino Scherrer Anirudh Goyal Stefan Bauer Yoshua Bengio Nan Rosemary Ke CML OOD BDL TTA 23 8 0 09 Jun 2022
BaCaDI: Bayesian Causal Discovery with Unknown Interventions Alexander Hagele Jonas Rothfuss Lars Lorch Vignesh Ram Somnath Bernhard Schölkopf Andreas Krause CML BDL 33 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 29 48 0 03 Mar 2022
Bayesian Structure Learning with Generative Flow Networks T. Deleu António Góis Chris C. Emezue M. Rankawat Simon Lacoste-Julien Stefan Bauer Yoshua Bengio BDL 34 143 0 28 Feb 2022
Learning Neural Causal Models with Active Interventions Nino Scherrer O. Bilaniuk Yashas Annadani Anirudh Goyal Patrick Schwab Bernhard Schölkopf Michael C. Mozer Yoshua Bengio Stefan Bauer Nan Rosemary Ke CML 28 42 0 06 Sep 2021
DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks Dennis L. Wei Tian Gao Yue Yu CML 56 71 0 18 Oct 2020