Tractable Uncertainty for Structure Learning

Tractable Uncertainty for Structure Learning

29 April 2022

Marta Z. Kwiatkowska

Papers citing "Tractable Uncertainty for Structure Learning"

10 / 10 papers shown

Title
ProDAG: Projected Variational Inference for Directed Acyclic Graphs Ryan Thompson Edwin V. Bonilla Robert Kohn 40 0 0 20 May 2025
Learning Structural Causal Models through Deep Generative Models: Methods, Guarantees, and Challenges Audrey Poinsot Alessandro Leite Nicolas Chesneau Michèle Sébag Marc Schoenauer 54 3 0 08 May 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
Characteristic Circuits Zhongjie Yu Martin Trapp Kristian Kersting TPM 20 5 0 12 Dec 2023
Subtractive Mixture Models via Squaring: Representation and Learning Lorenzo Loconte Aleksanteri Sladek Stefan Mengel Martin Trapp Arno Solin Nicolas Gillis Antonio Vergari TPM 41 21 0 01 Oct 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
GFlowNets for AI-Driven Scientific Discovery Moksh Jain T. Deleu Jason S. Hartford Cheng-Hao Liu Alex Hernandez-Garcia Yoshua Bengio AI4CE 34 45 0 01 Feb 2023
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 32 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 30 7 0 24 Oct 2022
BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery Chris Cundy Aditya Grover Stefano Ermon CML 40 72 0 06 Dec 2021