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DiBS: Differentiable Bayesian Structure Learning

25 May 2021

Papers citing "DiBS: Differentiable Bayesian Structure Learning"

50 / 66 papers shown

Title
Flow-Based Non-stationary Temporal Regime Causal Structure Learning Abdellah Rahmani P. Frossard AI4TS CML 24 0 0 20 Jun 2025
Identifying Causal Direction via Variational Bayesian Compression Quang-Duy Tran Bao Duong Phuoc Nguyen Thin Nguyen CML 119 0 0 12 May 2025
Causal Bayesian Optimization with Unknown Graphs Jean Durand Yashas Annadani Stefan Bauer S. Parbhoo CML 87 0 0 25 Mar 2025
ACTIVA: Amortized Causal Effect Estimation without Graphs via Transformer-based Variational Autoencoder Andreas Sauter Saber Salehkaleybar Aske Plaat Erman Acar CML 131 2 0 03 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 102 0 0 22 Feb 2025
Causal Temporal Regime Structure Learning Abdellah Rahmani Pascal Frossard CML 256 2 0 20 Feb 2025
Optimal Particle-based Approximation of Discrete Distributions (OPAD) Hadi Mohasel Afshar Gilad Francis Sally Cripps 63 0 0 30 Nov 2024
Generative Intervention Models for Causal Perturbation Modeling Nora Schneider Lars Lorch Niki Kilbertus Bernhard Schölkopf Andreas Krause 173 2 0 21 Nov 2024
Graph Agnostic Causal Bayesian Optimisation Sumantrak Mukherjee Mengyan Zhang Seth Flaxman Sebastian Vollmer CML 92 0 0 05 Nov 2024
Sample Efficient Bayesian Learning of Causal Graphs from Interventions Zihan Zhou Muhammad Qasim Elahi Murat Kocaoglu CML 82 0 0 26 Oct 2024
ExDBN: Exact learning of Dynamic Bayesian Networks Pavel Rytíř Ales Wodecki Georgios Korpas Jakub Mareˇcek CML 85 0 0 21 Oct 2024
Amortized Inference of Causal Models via Conditional Fixed-Point Iterations Divyat Mahajan Jannes Gladrow Agrin Hilmkil Cheng Zhang M. Scetbon 125 2 0 08 Oct 2024
Enhancing Solution Efficiency in Reinforcement Learning: Leveraging Sub-GFlowNet and Entropy Integration Siyi He 57 0 0 01 Oct 2024
Possible principles for aligned structure learning agents Lancelot Da Costa Tomáš Gavenčiak David Hyland Mandana Samiei Cristian Dragos-Manta Candice Pattisapu Adeel Razi Karl J. Friston 74 1 0 30 Sep 2024
Optimal Kernel Choice for Score Function-based Causal Discovery Wenjie Wang Erdun Gao Feng Liu Xinge You Tongliang Liu Kun Zhang Biwei Huang 69 3 0 14 Jul 2024
Scalable Variational Causal Discovery Unconstrained by Acyclicity Nu Hoang Bao Duong Thin Nguyen CML 90 0 0 06 Jul 2024
Enabling Causal Discovery in Post-Nonlinear Models with Normalizing Flows Nu Hoang Bao Duong Thin Nguyen 75 0 0 06 Jul 2024
Scalable Differentiable Causal Discovery in the Presence of Latent Confounders with Skeleton Posterior (Extended Version) Pingchuan Ma Rui Ding Qiang Fu Jiaru Zhang Shuai Wang Shi Han Dongmei Zhang CML 92 2 0 15 Jun 2024
Embarrassingly Parallel GFlowNets Tiago da Silva Luiz Max Carvalho Amauri Souza Samuel Kaski Diego Mesquita 154 1 0 05 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 83 4 0 05 Jun 2024
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 246 12 0 28 Feb 2024
Optimal Transport for Structure Learning Under Missing Data Vy Vo He Zhao Trung Le Edwin V. Bonilla Dinh Q. Phung CML 123 4 0 23 Feb 2024
Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders Christian Toth Christian Knoll Franz Pernkopf Robert Peharz CML 153 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 84 4 0 04 Feb 2024
Learning Socio-Temporal Graphs for Multi-Agent Trajectory Prediction Yuke Li Lixiong Chen Guan-Hong Chen Ching-Yao Chan Kun Zhang Stefano Anzellotti Donglai Wei 61 0 0 22 Dec 2023
Structure Learning with Adaptive Random Neighborhood Informed MCMC Alberto Caron Xitong Liang Samuel Livingstone Jim Griffin 31 2 0 01 Nov 2023
Benchmarking and Explaining Large Language Model-based Code Generation: A Causality-Centric Approach Zhenlan Ji Pingchuan Ma Zongjie Li Shuai Wang 70 23 0 10 Oct 2023
Discovering Mixtures of Structural Causal Models from Time Series Data Sumanth Varambally Yi-An Ma Rose Yu 112 6 0 10 Oct 2023
Causal structure learning with momentum: Sampling distributions over Markov Equivalence Classes of DAGs Moritz Schauer Marcel Wienöbst CML 90 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 73 4 0 05 Oct 2023
Estimation of Counterfactual Interventions under Uncertainties Juliane Weilbach S. Gerwinn M. Kandemir Martin Fraenzle 75 0 0 15 Sep 2023
Differentiable Bayesian Structure Learning with Acyclicity Assurance Quang-Duy Tran Phuoc Nguyen Bao Duong Thin Nguyen 76 2 0 04 Sep 2023
BayesDAG: Gradient-Based Posterior Inference for Causal Discovery Yashas Annadani Nick Pawlowski Joel Jennings Stefan Bauer Cheng Zhang Wenbo Gong CML BDL 98 19 0 26 Jul 2023
Identifiability Guarantees for Causal Disentanglement from Soft Interventions Jiaqi Zhang C. Squires Kristjan Greenewald Akash Srivastava Karthikeyan Shanmugam Caroline Uhler CML 129 65 0 12 Jul 2023
Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation Chris C. Emezue Alexandre Drouin T. Deleu Stefan Bauer Yoshua Bengio CML 84 2 0 11 Jul 2023
A Bayesian Take on Gaussian Process Networks Enrico Giudice Jack Kuipers G. Moffa GP 90 3 0 20 Jun 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 126 46 0 30 May 2023
Causality-Aided Trade-off Analysis for Machine Learning Fairness Zhenlan Ji Pingchuan Ma Shuai Wang Yanhui Li FaML 112 8 0 22 May 2023
Toward Falsifying Causal Graphs Using a Permutation-Based Test Elias Eulig Atalanti A. Mastakouri Patrick Blobaum Michael W. Hardt Dominik Janzing 35 13 0 16 May 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 80 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 103 25 0 08 Feb 2023
GFlowNets for AI-Driven Scientific Discovery Moksh Jain T. Deleu Jason S. Hartford Cheng-Hao Liu Alex Hernandez-Garcia Yoshua Bengio AI4CE 92 55 0 01 Feb 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 133 93 0 30 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 127 2 0 24 Nov 2022
Reinforcement Causal Structure Learning on Order Graph Dezhi Yang Guoxian Yu Jun Wang Zhe Wu Maozu Guo BDL CML 100 16 0 22 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 111 29 0 04 Nov 2022
Learning Discrete Directed Acyclic Graphs via Backpropagation A. Wren Pasquale Minervini Luca Franceschi Valentina Zantedeschi 56 2 0 27 Oct 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 94 7 0 24 Oct 2022
On the Identifiability and Estimation of Causal Location-Scale Noise Models Alexander Immer Christoph Schultheiss Julia E. Vogt Bernhard Schölkopf Peter Buhlmann Alexander Marx CML 107 36 0 13 Oct 2022
Active Learning for Optimal Intervention Design in Causal Models Jiaqi Zhang Louis V. Cammarata C. Squires T. Sapsis Caroline Uhler CML 109 28 0 10 Sep 2022