Amortized Inference for Causal Structure Learning

25 May 2022

Papers citing "Amortized Inference for Causal Structure Learning"

46 / 46 papers shown

Title
Identifying Causal Direction via Variational Bayesian Compression Quang-Duy Tran Bao Duong Phuoc Nguyen Thin Nguyen CML 26 0 0 12 May 2025
ACTIVA: Amortized Causal Effect Estimation without Graphs via Transformer-based Variational Autoencoder Andreas Sauter Saber Salehkaleybar Aske Plaat Erman Acar CML 43 0 0 03 Mar 2025
Amortized Conditional Independence Testing Bao Duong Nu Hoang T. Nguyen CML 45 0 0 28 Feb 2025
Learning Identifiable Structures Helps Avoid Bias in DNN-based Supervised Causal Learning Jiaru Zhang Rui Ding Qiang Fu Bojun Huang Zizhen Deng Yang Hua Haibing Guan Shi Han Dongmei Zhang CML 48 0 0 15 Feb 2025
Amortized In-Context Bayesian Posterior Estimation Sarthak Mittal Niels Leif Bracher Guillaume Lajoie P. Jaini Marcus A. Brubaker 54 1 0 10 Feb 2025
Sample Efficient Bayesian Learning of Causal Graphs from Interventions Zihan Zhou Muhammad Qasim Elahi Murat Kocaoglu CML 26 0 0 26 Oct 2024
Efficient Differentiable Discovery of Causal Order Mathieu Chevalley Arash Mehrjou Patrick Schwab 40 0 0 11 Oct 2024
Zero-Shot Learning of Causal Models Divyat Mahajan Jannes Gladrow Agrin Hilmkil Cheng Zhang M. Scetbon 36 1 0 08 Oct 2024
GAMformer: In-Context Learning for Generalized Additive Models Andreas Mueller Julien N. Siems Harsha Nori David Salinas Arber Zela Rich Caruana Frank Hutter AI4CE 31 3 0 06 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 20 1 0 30 Sep 2024
Interventional Causal Structure Discovery over Graphical Models with Convergence and Optimality Guarantees Qiu Chengbo Yang Kai CML 35 0 0 09 Aug 2024
MiranDa: Mimicking the Learning Processes of Human Doctors to Achieve Causal Inference for Medication Recommendation Ziheng Wang Xinhe Li H. Momma Stefan Köpsell CML 26 0 0 23 Jul 2024
Enabling Causal Discovery in Post-Nonlinear Models with Normalizing Flows Nu Hoang Bao Duong Thin Nguyen 22 0 0 06 Jul 2024
Disentangled Representations for Causal Cognition Filippo Torresan Manuel Baltieri CML 29 1 0 30 Jun 2024
Standardizing Structural Causal Models Weronika Ormaniec Scott Sussex Lars Lorch Bernhard Schölkopf Andreas Krause CML 47 5 0 17 Jun 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 50 2 0 15 Jun 2024
Causal Discovery over High-Dimensional Structured Hypothesis Spaces with Causal Graph Partitioning Ashka Shah Adela DePavia Nathaniel Hudson Ian T. Foster Rick L. Stevens CML 26 1 0 10 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 36 3 0 05 Jun 2024
Deriving Causal Order from Single-Variable Interventions: Guarantees & Algorithm Mathieu Chevalley Patrick Schwab Arash Mehrjou 30 1 0 28 May 2024
Demystifying amortized causal discovery with transformers Francesco Montagna Max Cairney-Leeming Dhanya Sridhar Francesco Locatello CML 57 1 0 27 May 2024
Amortized Active Causal Induction with Deep Reinforcement Learning Yashas Annadani P. Tigas Stefan Bauer Adam Foster 34 0 0 26 May 2024
CausalPlayground: Addressing Data-Generation Requirements in Cutting-Edge Causality Research Andreas Sauter Erman Acar Aske Plaat SyDa CML 34 1 0 21 May 2024
Accelerated Fully First-Order Methods for Bilevel and Minimax Optimization Chris Junchi Li 54 0 0 01 May 2024
FiP: a Fixed-Point Approach for Causal Generative Modeling M. Scetbon Joel Jennings Agrin Hilmkil Cheng Zhang Chao Ma 37 2 0 10 Apr 2024
Optimal Transport for Structure Learning Under Missing Data Vy Vo He Zhao Trung Le Edwin V. Bonilla Dinh Q. Phung CML 43 3 0 23 Feb 2024
Federated Causal Discovery from Heterogeneous Data Loka Li Ignavier Ng Gongxu Luo Biwei Huang Guan-Hong Chen Tongliang Liu Bin Gu Kun Zhang FedML 34 5 0 20 Feb 2024
Graph Structure Inference with BAM: Introducing the Bilinear Attention Mechanism Philipp Froehlich Heinz Koeppl GNN 16 1 0 12 Feb 2024
The Essential Role of Causality in Foundation World Models for Embodied AI Tarun Gupta Wenbo Gong Chao Ma Nick Pawlowski Agrin Hilmkil ... Jianfeng Gao Stefan Bauer Danica Kragic Bernhard Schölkopf Cheng Zhang 30 15 0 06 Feb 2024
Sample, estimate, aggregate: A recipe for causal discovery foundation models Menghua Wu Yujia Bao Regina Barzilay Tommi Jaakkola CML 41 7 0 02 Feb 2024
CORE: Towards Scalable and Efficient Causal Discovery with Reinforcement Learning Andreas Sauter N. Botteghi Erman Acar Aske Plaat CML 11 3 0 30 Jan 2024
Towards Causal Relationship in Indefinite Data: Baseline Model and New Datasets Hang Chen Xinyu Yang Keqing Du CML 26 2 0 16 Jan 2024
Stable Differentiable Causal Discovery Achille Nazaret Justin Hong Elham Azizi David M. Blei CML 18 9 0 17 Nov 2023
Distributionally Robust Skeleton Learning of Discrete Bayesian Networks Yeshu Li Brian D. Ziebart OOD 21 0 0 10 Nov 2023
Learned Causal Method Prediction Shantanu Gupta Cheng Zhang Agrin Hilmkil OOD 33 2 0 07 Nov 2023
Discovering Mixtures of Structural Causal Models from Time Series Data Sumanth Varambally Yi-An Ma Rose Yu 20 4 0 10 Oct 2023
Constraint-Free Structure Learning with Smooth Acyclic Orientations Riccardo Massidda Francesco Landolfi Martina Cinquini Davide Bacciu 25 6 0 15 Sep 2023
Differentiable Bayesian Structure Learning with Acyclicity Assurance Quang-Duy Tran Phuoc Nguyen Bao Duong Thin Nguyen 29 2 0 04 Sep 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
A Scale-Invariant Sorting Criterion to Find a Causal Order in Additive Noise Models Alexander G. Reisach Myriam Tami C. Seiler Antoine Chambaz S. Weichwald CML 31 19 0 31 Mar 2023
GFlowNets for AI-Driven Scientific Discovery Moksh Jain T. Deleu Jason S. Hartford Cheng-Hao Liu Alex Hernandez-Garcia Yoshua Bengio AI4CE 23 45 0 01 Feb 2023
Deep Causal Learning: Representation, Discovery and Inference Zizhen Deng Xiaolong Zheng Hu Tian D. Zeng CML BDL 26 11 0 07 Nov 2022
CausalBench: A Large-scale Benchmark for Network Inference from Single-cell Perturbation Data Mathieu Chevalley Yusuf Roohani Arash Mehrjou J. Leskovec Patrick Schwab CML 21 36 0 31 Oct 2022
MARS: Meta-Learning as Score Matching in the Function Space Krunoslav Lehman Pavasovic Jonas Rothfuss Andreas Krause BDL 18 4 0 24 Oct 2022
Learning Multiscale Non-stationary Causal Structures Gabriele DÁcunto G. D. F. Morales P. Bajardi Francesco Bonchi CML AI4TS 32 3 0 31 Aug 2022
TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second Noah Hollmann Samuel G. Müller Katharina Eggensperger Frank Hutter 25 260 0 05 Jul 2022
From Ordinary Differential Equations to Structural Causal Models: the deterministic case Joris Mooij Dominik Janzing Bernhard Schölkopf 68 101 0 09 Aug 2014