Variational Causal Networks: Approximate Bayesian Inference over Causal Structures

14 June 2021

Stefan Bauer

Papers citing "Variational Causal Networks: Approximate Bayesian Inference over Causal Structures"

34 / 34 papers shown

Title
Causal Bayesian Optimization with Unknown Graphs Jean Durand Yashas Annadani Stefan Bauer S. Parbhoo CML 63 0 0 25 Mar 2025
Enhancing Solution Efficiency in Reinforcement Learning: Leveraging Sub-GFlowNet and Entropy Integration Siyi He 28 0 0 01 Oct 2024
Disentangled Representations for Causal Cognition Filippo Torresan Manuel Baltieri CML 35 1 0 30 Jun 2024
Challenges and Considerations in the Evaluation of Bayesian Causal Discovery Amir Mohammad Karimi Mamaghan P. Tigas Karl Henrik Johansson Yarin Gal Yashas Annadani Stefan Bauer CML 42 3 0 05 Jun 2024
ProDAG: Projection-Induced Variational Inference for Directed Acyclic Graphs Ryan Thompson Edwin V. Bonilla Robert Kohn 40 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
Variational DAG Estimation via State Augmentation With Stochastic Permutations Edwin V. Bonilla P. Elinas He Zhao Maurizio Filippone V. Kitsios Terry O'Kane CML 43 3 0 04 Feb 2024
Causal structure learning with momentum: Sampling distributions over Markov Equivalence Classes of DAGs Moritz Schauer Marcel Wienöbst CML 22 2 0 09 Oct 2023
Causal Inference in Gene Regulatory Networks with GFlowNet: Towards Scalability in Large Systems Trang Nguyen Alexander Tong Kanika Madan Yoshua Bengio Dianbo Liu 24 4 0 05 Oct 2023
BayesDAG: Gradient-Based Posterior Inference for Causal Discovery Yashas Annadani Nick Pawlowski Joel Jennings Stefan Bauer Cheng Zhang Wenbo Gong CML BDL 13 17 0 26 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 32 43 0 30 May 2023
CO-BED: Information-Theoretic Contextual Optimization via Bayesian Experimental Design Desi R. Ivanova Joel Jennings Tom Rainforth Cheng Zhang Adam Foster 29 3 0 27 Feb 2023
Differentiable Multi-Target Causal Bayesian Experimental Design Yashas Annadani P. Tigas Desi R. Ivanova Andrew Jesson Y. Gal Adam Foster Stefan Bauer BDL CML 23 13 0 21 Feb 2023
DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets Lazar Atanackovic Alexander Tong Bo Wang Leo J. Lee Yoshua Bengio Jason S. Hartford BDL 29 21 0 08 Feb 2023
Disentanglement of Latent Representations via Causal Interventions Gael Gendron Michael Witbrock Gillian Dobbie OOD CML CoGe 18 2 0 02 Feb 2023
GFlowNets for AI-Driven Scientific Discovery Moksh Jain T. Deleu Jason S. Hartford Cheng-Hao Liu Alex Hernandez-Garcia Yoshua Bengio AI4CE 31 45 0 01 Feb 2023
A Survey of Methods, Challenges and Perspectives in Causality Gael Gendron Michael Witbrock Gillian Dobbie OOD AI4CE CML 19 12 0 01 Feb 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 35 2 0 24 Nov 2022
Bayesian learning of Causal Structure and Mechanisms with GFlowNets and Variational Bayes Mizu Nishikawa-Toomey T. Deleu Jithendaraa Subramanian Yoshua Bengio Laurent Charlin BDL CML 29 29 0 04 Nov 2022
Learning Latent Structural Causal Models Jithendaraa Subramanian Yashas Annadani Ivaxi Sheth Nan Rosemary Ke T. Deleu Stefan Bauer Derek Nowrouzezahrai Samira Ebrahimi Kahou CML 27 7 0 24 Oct 2022
Learning Multiscale Non-stationary Causal Structures Gabriele DÁcunto G. D. F. Morales P. Bajardi Francesco Bonchi CML AI4TS 43 3 0 31 Aug 2022
Latent Variable Models for Bayesian Causal Discovery Jithendaraa Subramanian Yashas Annadani Ivaxi Sheth Stefan Bauer Derek Nowrouzezahrai Samira Ebrahimi Kahou CML BDL 28 1 0 12 Jul 2022
Efficient Real-world Testing of Causal Decision Making via Bayesian Experimental Design for Contextual Optimisation Desi R. Ivanova Joel Jennings Cheng Zhang Adam Foster CML 16 2 0 12 Jul 2022
TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second Noah Hollmann Samuel G. Müller Katharina Eggensperger Frank Hutter 30 260 0 05 Jul 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 31 8 0 09 Jun 2022
Active Bayesian Causal Inference Christian Toth Lars Lorch Christian Knoll Andreas Krause Franz Pernkopf Robert Peharz Julius von Kügelgen 45 26 0 04 Jun 2022
BaCaDI: Bayesian Causal Discovery with Unknown Interventions Alexander Hagele Jonas Rothfuss Lars Lorch Vignesh Ram Somnath Bernhard Schölkopf Andreas Krause CML BDL 44 19 0 03 Jun 2022
Tractable Uncertainty for Structure Learning Benjie Wang Matthew Wicker Marta Z. Kwiatkowska CML TPM 20 11 0 29 Apr 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 34 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 48 143 0 28 Feb 2022
GeneDisco: A Benchmark for Experimental Design in Drug Discovery Arash Mehrjou Ashkan Soleymani Andrew Jesson Pascal Notin Y. Gal Stefan Bauer Patrick Schwab 18 19 0 22 Oct 2021
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 43 42 0 06 Sep 2021
Causal Graph Discovery from Self and Mutually Exciting Time Series S. Wei Yao Xie C. Josef Rishikesan Kamaleswaran CML 27 2 0 04 Jun 2021
Parameter Priors for Directed Acyclic Graphical Models and the Characterization of Several Probability Distributions D. Geiger David Heckerman 117 195 0 05 May 2021