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On the Convergence of Continuous Constrained Optimization for Structure Learning
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
23 November 2020
Ignavier Ng
Sébastien Lachapelle
Nan Rosemary Ke
Damien Scieur
Kun Zhang
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Papers citing
"On the Convergence of Continuous Constrained Optimization for Structure Learning"
36 / 36 papers shown
Humanoid-inspired Causal Representation Learning for Domain Generalization
Ze Tao
Jian Zhang
Haowei Li
Xianshuai Li
Yifei Peng
Xiyao Liu
Senzhang Wang
Chao Liu
Sheng Ren
Shichao Zhang
155
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0
18 Oct 2025
Score-based Greedy Search for Structure Identification of Partially Observed Linear Causal Models
Xinshuai Dong
Ignavier Ng
Haoyue Dai
Jiaqi Sun
Xiangchen Song
Peter Spirtes
Kun Zhang
CML
162
1
0
05 Oct 2025
Differentiable Structure Learning and Causal Discovery for General Binary Data
Chang Deng
Bryon Aragam
227
0
0
25 Sep 2025
Analytic DAG Constraints for Differentiable DAG Learning
International Conference on Learning Representations (ICLR), 2025
Zhen Zhang
Ignavier Ng
Dong Gong
Yuhang Liu
Mingming Gong
Zhen Zhang
Kun Zhang
Anton van den Hengel
Javen Qinfeng Shi
CML
328
6
0
24 Mar 2025
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DAG: Projected Stochastic Approximation Iteration for DAG Structure Learning
Klea Ziu
Slavomír Hanzely
Loka Li
Kun Zhang
Martin Takáč
Dmitry Kamzolov
365
4
0
31 Oct 2024
Revisiting Differentiable Structure Learning: Inconsistency of
ℓ
1
\ell_1
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1
Penalty and Beyond
Kaifeng Jin
Ignavier Ng
Kun Zhang
Zhen Zhang
388
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0
24 Oct 2024
Causal Representation Learning in Temporal Data via Single-Parent Decoding
Philippe Brouillard
Sébastien Lachapelle
Julia Kaltenborn
Yaniv Gurwicz
Dhanya Sridhar
Alexandre Drouin
Peer Nowack
Jakob Runge
David Rolnick
CML
262
9
0
09 Oct 2024
Markov Equivalence and Consistency in Differentiable Structure Learning
Neural Information Processing Systems (NeurIPS), 2024
Chang Deng
Kevin Bello
Pradeep Ravikumar
Bryon Aragam
CML
607
0
0
08 Oct 2024
Interventional Causal Structure Discovery over Graphical Models with Convergence and Optimality Guarantees
IEEE Transactions on Network Science and Engineering (TNSE), 2024
Qiu Chengbo
Yang Kai
CML
283
3
0
09 Aug 2024
Causality for Tabular Data Synthesis: A High-Order Structure Causal Benchmark Framework
Ruibo Tu
Zineb Senane
Lele Cao
Cheng Zhang
Hedvig Kjellström
G. Henter
CML
508
6
0
12 Jun 2024
Optimal Transport for Structure Learning Under Missing Data
Vy Vo
He Zhao
Trung Le
Edwin V. Bonilla
Dinh Q. Phung
CML
361
6
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23 Feb 2024
Federated Causal Discovery from Heterogeneous Data
Loka Li
Ignavier Ng
Gongxu Luo
Erdun Gao
Guan-Hong Chen
Tongliang Liu
Bin Gu
Kun Zhang
FedML
336
16
0
20 Feb 2024
Boosting Causal Additive Models
Maximilian Kertel
Nadja Klein
310
0
0
12 Jan 2024
Effective Causal Discovery under Identifiable Heteroscedastic Noise Model
Naiyu Yin
Tian Gao
Yue Yu
Qiang Ji
CML
424
4
0
20 Dec 2023
Stable Differentiable Causal Discovery
Achille Nazaret
Justin Hong
Elham Azizi
David M. Blei
CML
483
28
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17 Nov 2023
Tree Search in DAG Space with Model-based Reinforcement Learning for Causal Discovery
Victor-Alexandru Darvariu
Stephen Hailes
Mirco Musolesi
CML
454
3
0
20 Oct 2023
Constraint-Free Structure Learning with Smooth Acyclic Orientations
International Conference on Learning Representations (ICLR), 2023
Riccardo Massidda
Francesco Landolfi
Martina Cinquini
Davide Bacciu
407
10
0
15 Sep 2023
Global Optimality in Bivariate Gradient-based DAG Learning
Neural Information Processing Systems (NeurIPS), 2023
Chang Deng
Kevin Bello
Bryon Aragam
Pradeep Ravikumar
282
11
0
30 Jun 2023
MM-DAG: Multi-task DAG Learning for Multi-modal Data -- with Application for Traffic Congestion Analysis
Knowledge Discovery and Data Mining (KDD), 2023
Tian-Shing Lan
Ziyue Li
Zhishuai Li
Mengwei He
Man Li
Fugee Tsung
W. Ketter
Rui Zhao
Chen Zhang
220
20
0
05 Jun 2023
Optimizing NOTEARS Objectives via Topological Swaps
International Conference on Machine Learning (ICML), 2023
Chang Deng
Kevin Bello
Bryon Aragam
Pradeep Ravikumar
167
23
0
26 May 2023
Discovering Causal Relations and Equations from Data
Physics reports (Phys. Rep.), 2023
Gustau Camps-Valls
Andreas Gerhardus
Urmi Ninad
Gherardo Varando
Georg Martius
E. Balaguer-Ballester
Ricardo Vinuesa
Emiliano Díaz
L. Zanna
Jakob Runge
PINN
AI4Cl
AI4CE
CML
292
125
0
21 May 2023
Structure Learning with Continuous Optimization: A Sober Look and Beyond
CLEaR (CLEaR), 2023
Ignavier Ng
Erdun Gao
Kun Zhang
CML
458
34
0
04 Apr 2023
Causal Discovery from Temporal Data: An Overview and New Perspectives
ACM Computing Surveys (ACM Comput. Surv.), 2023
Chang Gong
Di Yao
Chuzhe Zhang
Wenbin Li
Jingping Bi
AI4TS
CML
455
65
0
17 Mar 2023
Boosting Differentiable Causal Discovery via Adaptive Sample Reweighting
An Zhang
Fang Liu
Wenchang Ma
Zhibo Cai
Xiang Wang
Tat-Seng Chua
CML
318
8
0
06 Mar 2023
DAG Learning on the Permutahedron
International Conference on Learning Representations (ICLR), 2023
Valentina Zantedeschi
Luca Franceschi
Jean Kaddour
Matt J. Kusner
Vlad Niculae
358
12
0
27 Jan 2023
Evaluation of Induced Expert Knowledge in Causal Structure Learning by NOTEARS
International Conference on Pattern Recognition Applications and Methods (ICPRAM), 2023
Jawad Chowdhury
Rezaur Rashid
G. Terejanu
CML
295
14
0
04 Jan 2023
DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization
Neural Information Processing Systems (NeurIPS), 2022
Kevin Bello
Bryon Aragam
Pradeep Ravikumar
485
151
0
16 Sep 2022
On the Sparse DAG Structure Learning Based on Adaptive Lasso
Danru Xu
Erdun Gao
Wei Huang
Menghan Wang
Andy Song
Biwei Huang
CML
405
5
0
07 Sep 2022
Truncated Matrix Power Iteration for Differentiable DAG Learning
Neural Information Processing Systems (NeurIPS), 2022
Zhen Zhang
Ignavier Ng
Dong Gong
Yuhang Liu
Ehsan Abbasnejad
Biwei Huang
Kun Zhang
Javen Qinfeng Shi
326
31
0
30 Aug 2022
Differentiable and Transportable Structure Learning
International Conference on Machine Learning (ICML), 2022
Jeroen Berrevoets
Nabeel Seedat
F. Imrie
M. Schaar
472
4
0
13 Jun 2022
FedDAG: Federated DAG Structure Learning
Erdun Gao
Junjia Chen
Li Shen
Tongliang Liu
Biwei Huang
H. Bondell
FedML
375
23
0
07 Dec 2021
Towards Federated Bayesian Network Structure Learning with Continuous Optimization
Ignavier Ng
Kun Zhang
FedML
348
46
0
18 Oct 2021
DiBS: Differentiable Bayesian Structure Learning
Neural Information Processing Systems (NeurIPS), 2021
Lars Lorch
Jonas Rothfuss
Bernhard Schölkopf
Andreas Krause
449
117
0
25 May 2021
Inference of Causal Effects when Control Variables are Unknown
Conference on Uncertainty in Artificial Intelligence (UAI), 2020
Ludvig Hult
Dave Zachariah
CML
296
0
0
15 Dec 2020
Causal Discovery with Multi-Domain LiNGAM for Latent Factors
International Joint Conference on Artificial Intelligence (IJCAI), 2020
Yan Zeng
Shohei Shimizu
Ruichu Cai
Feng Xie
Michio Yamamoto
Zijian Li
CML
343
24
0
19 Sep 2020
On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
Ignavier Ng
AmirEmad Ghassami
Kun Zhang
CML
670
247
0
17 Jun 2020
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