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On the Role of Sparsity and DAG Constraints for Learning Linear DAGs

17 June 2020

Papers citing "On the Role of Sparsity and DAG Constraints for Learning Linear DAGs"

35 / 85 papers shown

Title
On the Role of Entropy-based Loss for Learning Causal Structures with Continuous Optimization Weilin Chen Jie Qiao Ruichu Cai Zijian Li CML 66 3 0 05 Jun 2021
DiBS: Differentiable Bayesian Structure Learning Lars Lorch Jonas Rothfuss Bernhard Schölkopf Andreas Krause 86 91 0 25 May 2021
Data Generating Process to Evaluate Causal Discovery Techniques for Time Series Data A. Lawrence Marcus Kaiser Rui Sampaio Maksim Sipos CML AI4TS 109 20 0 16 Apr 2021
Unsuitability of NOTEARS for Causal Graph Discovery Marcus Kaiser Maksim Sipos CML 109 66 0 12 Apr 2021
Deconfounded Score Method: Scoring DAGs with Dense Unobserved Confounding Alexis Bellot M. Schaar CML 75 11 0 28 Mar 2021
D'ya like DAGs? A Survey on Structure Learning and Causal Discovery M. Vowels Necati Cihan Camgöz Richard Bowden CML 147 305 0 03 Mar 2021
Beware of the Simulated DAG! Causal Discovery Benchmarks May Be Easy To Game Alexander G. Reisach C. Seiler S. Weichwald CML 82 142 0 26 Feb 2021
On the Convergence of Continuous Constrained Optimization for Structure Learning Ignavier Ng Sébastien Lachapelle Nan Rosemary Ke Simon Lacoste-Julien Kun Zhang 105 38 0 23 Nov 2020
A Bregman Method for Structure Learning on Sparse Directed Acyclic Graphs Manon Romain Alexandre d’Aspremont 19 5 0 05 Nov 2020
Array Programming with NumPy Charles R. Harris K. Millman S. Walt R. Gommers Pauli Virtanen ... Tyler Reddy Warren Weckesser Hameer Abbasi C. Gohlke T. Oliphant 205 15,182 0 18 Jun 2020
On Low Rank Directed Acyclic Graphs and Causal Structure Learning Zhuangyan Fang Shengyu Zhu Jiji Zhang Yue Liu Zhitang Chen Yangbo He CML 89 28 0 10 Jun 2020
DYNOTEARS: Structure Learning from Time-Series Data Roxana Pamfil Nisara Sriwattanaworachai Shaan Desai Philip Pilgerstorfer Paul Beaumont K. Georgatzis Bryon Aragam CML AI4TS BDL 109 192 0 02 Feb 2020
A Graph Autoencoder Approach to Causal Structure Learning Ignavier Ng Shengyu Zhu Zhitang Chen Zhuangyan Fang BDL CML 77 83 0 18 Nov 2019
Characterizing Distribution Equivalence and Structure Learning for Cyclic and Acyclic Directed Graphs AmirEmad Ghassami Alan Yang Negar Kiyavash Kun Zhang 81 2 0 28 Oct 2019
Masked Gradient-Based Causal Structure Learning Ignavier Ng Shengyu Zhu Zhuangyan Fang Haoyang Li Zhitang Chen Jun Wang CML 149 117 0 18 Oct 2019
Learning Sparse Nonparametric DAGs Xun Zheng Chen Dan Bryon Aragam Pradeep Ravikumar Eric Xing CML 180 261 0 29 Sep 2019
Causal Discovery with Reinforcement Learning Shengyu Zhu Ignavier Ng Zhitang Chen CML 89 241 0 11 Jun 2019
Gradient-Based Neural DAG Learning Sébastien Lachapelle P. Brouillard T. Deleu Simon Lacoste-Julien BDL CML 103 276 0 05 Jun 2019
DAG-GNN: DAG Structure Learning with Graph Neural Networks Yue Yu Jie Chen Tian Gao Mo Yu BDL CML GNN 89 490 0 22 Apr 2019
Structural Agnostic Modeling: Adversarial Learning of Causal Graphs Diviyan Kalainathan Olivier Goudet Isabelle M Guyon David Lopez-Paz Michèle Sebag CML 80 96 0 13 Mar 2018
DAGs with NO TEARS: Continuous Optimization for Structure Learning Xun Zheng Bryon Aragam Pradeep Ravikumar Eric Xing NoLa CML OffRL 109 951 0 04 Mar 2018
TensorFlow: A system for large-scale machine learning Martín Abadi P. Barham Jianmin Chen Zhiwen Chen Andy Davis ... Vijay Vasudevan Pete Warden Martin Wicke Yuan Yu Xiaoqiang Zhang GNN AI4CE 438 18,361 0 27 May 2016
Large-scale Log-determinant Computation through Stochastic Chebyshev Expansions Insu Han Dmitry Malioutov Jinwoo Shin 66 96 0 22 Mar 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.3K 150,577 0 22 Dec 2014
Concave Penalized Estimation of Sparse Gaussian Bayesian Networks Bryon Aragam Qing Zhou CML 132 107 0 04 Jan 2014
Structural Intervention Distance (SID) for Evaluating Causal Graphs J. Peters Peter Buhlmann CML 104 40 0 05 Jun 2013
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data David Heckerman D. Geiger D. M. Chickering TPM 123 3,985 0 27 Feb 2013
Causal Inference in the Presence of Latent Variables and Selection Bias Peter Spirtes Christopher Meek Thomas S. Richardson CML 206 448 0 20 Feb 2013
A Polynomial-Time Algorithm for Deciding Markov Equivalence of Directed Cyclic Graphical Models Thomas S. Richardson 124 45 0 13 Feb 2013
Ordering-Based Search: A Simple and Effective Algorithm for Learning Bayesian Networks M. Teyssier D. Koller 178 375 0 04 Jul 2012
Adjacency-Faithfulness and Conservative Causal Inference Joseph Ramsey Jiji Zhang Peter Spirtes 121 276 0 27 Jun 2012
$$\ell_0$-penalized maximum likelihood for sparse directed acyclic graphs$ $\ell_0$ -penalized maximum likelihood for sparse directed acyclic graphs Sara van de Geer Peter Buhlmann CML 182 83 0 24 May 2012
Identifiability of Gaussian structural equation models with equal error variances J. Peters Peter Buhlmann CML 208 339 0 11 May 2012
Learning high-dimensional directed acyclic graphs with latent and selection variables Diego Colombo Marloes H. Maathuis M. Kalisch Thomas S. Richardson CML 134 468 0 29 Apr 2011
DirectLiNGAM: A direct method for learning a linear non-Gaussian structural equation model Shohei Shimizu Takanori Inazumi Yasuhiro Sogawa Aapo Hyvarinen Yoshinobu Kawahara Takashi Washio P. Hoyer K. Bollen CML 106 519 0 13 Jan 2011