BayesDAG: Gradient-Based Posterior Inference for Causal Discovery

BayesDAG: Gradient-Based Posterior Inference for Causal Discovery

26 July 2023

Yashas Annadani

Stefan Bauer

Cheng Zhang

Papers citing "BayesDAG: Gradient-Based Posterior Inference for Causal Discovery"

16 / 16 papers shown

Title
Causal Bayesian Optimization with Unknown Graphs Jean Durand Yashas Annadani Stefan Bauer S. Parbhoo CML 63 0 0 25 Mar 2025
Since Faithfulness Fails: The Performance Limits of Neural Causal Discovery Mateusz Olko Mateusz Gajewski Joanna Wojciechowska Mikołaj Morzy Piotr Sankowski Piotr Miłoś CML 47 0 0 22 Feb 2025
Sample Efficient Bayesian Learning of Causal Graphs from Interventions Zihan Zhou Muhammad Qasim Elahi Murat Kocaoglu CML 36 0 0 26 Oct 2024
LOCAL: Learning with Orientation Matrix to Infer Causal Structure from Time Series Data Yue Cheng Jiajun Zhang Weiwei Xing Xiaoyu Guo Yue Cheng Witold Pedrycz CML 32 0 0 25 Oct 2024
Efficient Differentiable Discovery of Causal Order Mathieu Chevalley Arash Mehrjou Patrick Schwab 45 0 0 11 Oct 2024
Variational Search Distributions Daniel M. Steinberg Rafael Oliveira Cheng Soon Ong Edwin V. Bonilla 33 0 0 10 Sep 2024
Scalable Variational Causal Discovery Unconstrained by Acyclicity Nu Hoang Bao Duong Thin Nguyen CML 58 0 0 06 Jul 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
Bayesian Vector AutoRegression with Factorised Granger-Causal Graphs He Zhao V. Kitsios Terry O'Kane Edwin V. Bonilla CML 24 1 0 06 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
Discrete Langevin Sampler via Wasserstein Gradient Flow Haoran Sun H. Dai Bo Dai Haomin Zhou Dale Schuurmans BDL 42 19 0 29 Jun 2022
BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery Chris Cundy Aditya Grover Stefano Ermon CML 40 72 0 06 Dec 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
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators Changyou Chen Nan Ding Lawrence Carin 34 158 0 21 Oct 2016