Efficient Neural Causal Discovery without Acyclicity Constraints

22 July 2021

Papers citing "Efficient Neural Causal Discovery without Acyclicity Constraints"

35 / 35 papers shown

Title
IGDA: Interactive Graph Discovery through Large Language Model Agents Alex Havrilla David Alvarez-Melis Nicolò Fusi AI4CE 59 0 0 24 Feb 2025
Causal Discovery via Bayesian Optimization Bao Duong Sunil Gupta Thin Nguyen 79 0 0 28 Jan 2025
Zero-Shot Learning of Causal Models Divyat Mahajan Jannes Gladrow Agrin Hilmkil Cheng Zhang M. Scetbon 82 1 0 08 Oct 2024
Score matching through the roof: linear, nonlinear, and latent variables causal discovery Francesco Montagna P. M. Faller Patrick Bloebaum Elke Kirschbaum Francesco Locatello CML 113 0 0 26 Jul 2024
Demystifying amortized causal discovery with transformers Francesco Montagna Max Cairney-Leeming Dhanya Sridhar Francesco Locatello CML 89 1 0 27 May 2024
Sample, estimate, aggregate: A recipe for causal discovery foundation models Menghua Wu Yujia Bao Regina Barzilay Tommi Jaakkola CML 65 7 0 02 Feb 2024
Towards Causal Representation Learning Bernhard Schölkopf Francesco Locatello Stefan Bauer Nan Rosemary Ke Nal Kalchbrenner Anirudh Goyal Yoshua Bengio OOD CML AI4CE 89 320 0 22 Feb 2021
Differentiable Causal Discovery from Interventional Data P. Brouillard Sébastien Lachapelle Alexandre Lacoste Simon Lacoste-Julien Alexandre Drouin CML 40 184 0 03 Jul 2020
On the Role of Sparsity and DAG Constraints for Learning Linear DAGs Ignavier Ng AmirEmad Ghassami Kun Zhang CML 44 189 0 17 Jun 2020
Learning DAGs without imposing acyclicity Gherardo Varando CML 33 12 0 04 Jun 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 261 42,038 0 03 Dec 2019
Learning Neural Causal Models from Unknown Interventions Nan Rosemary Ke O. Bilaniuk Anirudh Goyal Stefan Bauer Hugo Larochelle Bernhard Schölkopf Michael C. Mozer C. Pal Yoshua Bengio CML OOD 79 168 0 02 Oct 2019
Learning Sparse Nonparametric DAGs Xun Zheng Chen Dan Bryon Aragam Pradeep Ravikumar Eric Xing CML 137 257 0 29 Sep 2019
Flow Models for Arbitrary Conditional Likelihoods Yongqian Li Shoaib Akbar Junier B. Oliva OOD AI4CE 21 39 0 13 Sep 2019
Causal Discovery with Reinforcement Learning Shengyu Zhu Ignavier Ng Zhitang Chen CML 40 239 0 11 Jun 2019
Gradient-Based Neural DAG Learning Sébastien Lachapelle P. Brouillard T. Deleu Simon Lacoste-Julien BDL CML 43 270 0 05 Jun 2019
DAG-GNN: DAG Structure Learning with Graph Neural Networks Yue Yu Jie Chen Tian Gao Mo Yu BDL CML GNN 64 481 0 22 Apr 2019
Causal Discovery with General Non-Linear Relationships Using Non-Linear ICA R. Monti Kun Zhang Aapo Hyvarinen CML 42 91 0 19 Apr 2019
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms Yoshua Bengio T. Deleu Nasim Rahaman Nan Rosemary Ke Sébastien Lachapelle O. Bilaniuk Anirudh Goyal C. Pal CML OOD 86 334 0 30 Jan 2019
GAIN: Missing Data Imputation using Generative Adversarial Nets Jinsung Yoon James Jordon M. Schaar GAN 37 1,001 0 07 Jun 2018
Variational Autoencoder with Arbitrary Conditioning Oleg Ivanov Michael Figurnov Dmitry Vetrov BDL DRL 37 146 0 06 Jun 2018
Neural Autoregressive Flows Chin-Wei Huang David M. Krueger Alexandre Lacoste Aaron Courville DRL AI4CE 84 439 0 03 Apr 2018
DAGs with NO TEARS: Continuous Optimization for Structure Learning Xun Zheng Bryon Aragam Pradeep Ravikumar Eric Xing NoLa CML OffRL 59 925 0 04 Mar 2018
Characterizing and Learning Equivalence Classes of Causal DAGs under Interventions Karren D. Yang Abigail Katoff Caroline Uhler CML 17 102 0 17 Feb 2018
Causal Generative Neural Networks Olivier Goudet Diviyan Kalainathan Philippe Caillou Isabelle M Guyon David Lopez-Paz Michèle Sebag BDL CML DRL 43 59 0 24 Nov 2017
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 252 4,143 0 21 May 2015
Causal inference using invariant prediction: identification and confidence intervals J. Peters Peter Buhlmann N. Meinshausen OOD 88 961 0 06 Jan 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 811 149,474 0 22 Dec 2014
Constraint-based Causal Discovery from Multiple Interventions over Overlapping Variable Sets Sofia Triantafillou Ioannis Tsamardinos CML 109 149 0 10 Mar 2014
Structural Intervention Distance (SID) for Evaluating Causal Graphs J. Peters Peter Buhlmann CML 68 40 0 05 Jun 2013
On the Number of Experiments Sufficient and in the Worst Case Necessary to Identify All Causal Relations Among N Variables F. Eberhardt Clark Glymour R. Scheines 60 153 0 04 Jul 2012
On Causal and Anticausal Learning Bernhard Schölkopf Dominik Janzing J. Peters Eleni Sgouritsa Kun Zhang Joris Mooij CML 71 604 0 27 Jun 2012
Almost Optimal Intervention Sets for Causal Discovery F. Eberhardt CML 66 59 0 13 Jun 2012
Characterization and Greedy Learning of Interventional Markov Equivalence Classes of Directed Acyclic Graphs Alain Hauser Peter Buhlmann CML 63 425 0 14 Apr 2011
Learning Bayesian Networks with the bnlearn R Package M. Scutari BDL 130 1,723 0 26 Aug 2009