DYNOTEARS: Structure Learning from Time-Series Data

2 February 2020

Roxana Pamfil

Nisara Sriwattanaworachai

Papers citing "DYNOTEARS: Structure Learning from Time-Series Data"

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Title
Adapt3R: Adaptive 3D Scene Representation for Domain Transfer in Imitation Learning Albert Wilcox Mohamed Ghanem Masoud Moghani Pierre Barroso Benjamin Joffe Animesh Garg 50 0 0 06 Mar 2025
Causal Temporal Regime Structure Learning Abdellah Rahmani Pascal Frossard CML 93 2 0 20 Feb 2025
SpaceTime: Causal Discovery from Non-Stationary Time Series Sarah Mameche Lénaïg Cornanguer Urmi Ninad Jilles Vreeken CML AI4TS 49 0 0 20 Jan 2025
LOCAL: Learning with Orientation Matrix to Infer Causal Structure from Time Series Data Yue Cheng Jiajun Zhang Weiwei Xing Xiaoyu Guo Yue Cheng Witold Pedrycz CML 34 0 0 25 Oct 2024
Sortability of Time Series Data Christopher Lohse Jonas Wahl CML 47 1 0 18 Jul 2024
CausalMMM: Learning Causal Structure for Marketing Mix Modeling Chang Gong Di Yao Lei Zhang Sheng Chen Wenbin Li Yueyang Su Jingping Bi 39 5 0 24 Jun 2024
ExDAG: Exact learning of DAGs Pavel Rytír Ales Wodecki Jakub Marecek CML 48 1 0 21 Jun 2024
Standardizing Structural Causal Models Weronika Ormaniec Scott Sussex Lars Lorch Bernhard Schölkopf Andreas Krause CML 58 5 0 17 Jun 2024
Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes Georg Manten Cecilia Casolo E. Ferrucci Søren Wengel Mogensen C. Salvi Niki Kilbertus CML BDL 46 8 0 28 Feb 2024
Towards Automated Causal Discovery: a case study on 5G telecommunication data Konstantina Biza Antonios Ntroumpogiannis Sofia Triantafillou Ioannis Tsamardinos 36 0 0 22 Feb 2024
Enhancing the Performance of Neural Networks Through Causal Discovery and Integration of Domain Knowledge Xiaoge Zhang Xiao-Lin Wang Fenglei Fan Yiu-ming Cheung Indranil Bose 38 1 0 29 Nov 2023
Discovering Mixtures of Structural Causal Models from Time Series Data Sumanth Varambally Yi Ma Rose Yu 22 5 0 10 Oct 2023
CausalTime: Realistically Generated Time-series for Benchmarking of Causal Discovery Yuxiao Cheng Ziqian Wang Tingxiong Xiao Qin Zhong J. Suo Kunlun He AI4TS CML 30 11 0 03 Oct 2023
Case Studies of Causal Discovery from IT Monitoring Time Series Ali Aït-Bachir Charles K. Assaad Christophe de Bignicourt Emilie Devijver Simon Ferreira Éric Gaussier Hosein Mohanna Lei Zan CML AI4TS 36 8 0 28 Jul 2023
Learning DAGs from Data with Few Root Causes Panagiotis Misiakos Chris Wendler Markus Püschel CML 44 10 0 25 May 2023
Discovering Causal Relations and Equations from Data 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 51 75 0 21 May 2023
CUTS+: High-dimensional Causal Discovery from Irregular Time-series Yuxiao Cheng Lianglong Li Tingxiong Xiao Zongren Li Qionghai Dai J. Suo K. He CML BDL AI4TS 26 22 0 10 May 2023
On Learning Time Series Summary DAGs: A Frequency Domain Approach Aramayis Dallakyan CML AI4TS 30 3 0 17 Apr 2023
A Survey on Causal Discovery Methods for I.I.D. and Time Series Data Uzma Hasan Emam Hossain Md. Osman Gani CML AI4TS 37 24 0 27 Mar 2023
eCDANs: Efficient Temporal Causal Discovery from Autocorrelated and Non-stationary Data (Student Abstract) Muhammad Hasan Ferdous Uzma Hasan Md. Osman Gani 28 2 0 06 Mar 2023
CUTS: Neural Causal Discovery from Irregular Time-Series Data Yuxiao Cheng Runzhao Yang Tingxiong Xiao Zongren Li J. Suo K. He Qionghai Dai OOD BDL AI4TS CML 29 25 0 15 Feb 2023
DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets Lazar Atanackovic Alexander Tong Bo Wang Leo J. Lee Yoshua Bengio Jason S. Hartford BDL 34 22 0 08 Feb 2023
CDANs: Temporal Causal Discovery from Autocorrelated and Non-Stationary Time Series Data Muhammad Hasan Ferdous Uzma Hasan Md. Osman Gani CML 44 3 0 07 Feb 2023
Hierarchical Graph Neural Networks for Causal Discovery and Root Cause Localization Dongjie Wang Zhengzhang Chen Jingchao Ni Liang Tong Zheng Wang Yanjie Fu Haifeng Chen AI4CE 13 17 0 03 Feb 2023
Evaluating Temporal Observation-Based Causal Discovery Techniques Applied to Road Driver Behaviour Rhys Howard Lars Kunze CML 25 7 0 31 Jan 2023
GDBN: a Graph Neural Network Approach to Dynamic Bayesian Network Yang Sun Yifan Xie BDL CML 34 1 0 28 Jan 2023
Causal Structural Learning from Time Series: A Convex Optimization Approach S. Wei Yao Xie CML 32 2 0 26 Jan 2023
Causal Recurrent Variational Autoencoder for Medical Time Series Generation Hongming Li Shujian Yu José C. Príncipe CML BDL MedIm 28 47 0 16 Jan 2023
Sensor data-driven analysis for identification of causal relationships between exposure to air pollution and respiratory rate in asthmatics D. Arvind S. Maiya 19 1 0 16 Jan 2023
On the Limit of Explaining Black-box Temporal Graph Neural Networks Minh Nhat Vu My T. Thai 26 4 0 02 Dec 2022
Directed Acyclic Graph Structure Learning from Dynamic Graphs Shaohua Fan Shuyang Zhang Xiao Wang Chuan Shi CML 39 5 0 30 Nov 2022
Estimation of a Causal Directed Acyclic Graph Process using Non-Gaussianity A. Einizade S. H. Sardouie CML 36 0 0 24 Nov 2022
Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks Yue Yu Xuan Kan Hejie Cui Ran Xu Yu Zheng ... Kun Zhang Razieh Nabi Ying Guo Chaogang Zhang Carl Yang 13 18 0 01 Nov 2022
Temporally Disentangled Representation Learning Weiran Yao Guangyi Chen Kun Zhang CML BDL OOD 32 49 0 24 Oct 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
DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization Kevin Bello Bryon Aragam Pradeep Ravikumar 66 78 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 32 4 0 07 Sep 2022
Truncated Matrix Power Iteration for Differentiable DAG Learning Zhen Zhang Ignavier Ng Dong Gong Yuhang Liu Ehsan Abbasnejad Biwei Huang Kun Zhang Javen Qinfeng Shi 37 25 0 30 Aug 2022
Achieving Long-Term Fairness in Sequential Decision Making Yaowei Hu Lu Zhang 25 20 0 04 Apr 2022
When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning Chuizheng Meng Sungyong Seo Defu Cao Sam Griesemer Yan Liu PINN AI4CE 51 57 0 31 Mar 2022
Multi-task Learning of Order-Consistent Causal Graphs Xinshi Chen Haoran Sun Caleb N. Ellington Eric Xing Le Song CML 27 15 0 03 Nov 2021
Towards Federated Bayesian Network Structure Learning with Continuous Optimization Ignavier Ng Kun Zhang FedML 47 38 0 18 Oct 2021
Causal Discovery from Conditionally Stationary Time Series Carles Balsells-Rodas Ruibo Tu Hedvig Kjellström Yingzhen Li Gabriele Schweikert Hedvig Kjellstrom Yingzhen Li BDL CML AI4TS 39 5 0 12 Oct 2021
Beyond Predictions in Neural ODEs: Identification and Interventions H. Aliee Fabian J. Theis Niki Kilbertus CML 43 24 0 23 Jun 2021
Neural graphical modelling in continuous-time: consistency guarantees and algorithms Alexis Bellot K. Branson M. Schaar CML AI4TS 26 44 0 06 May 2021
Data Generating Process to Evaluate Causal Discovery Techniques for Time Series Data A. Lawrence Marcus Kaiser Rui Sampaio Maksim Sipos CML AI4TS 37 17 0 16 Apr 2021
Unsuitability of NOTEARS for Causal Graph Discovery Marcus Kaiser Maksim Sipos CML 37 65 0 12 Apr 2021
D'ya like DAGs? A Survey on Structure Learning and Causal Discovery M. Vowels Necati Cihan Camgöz Richard Bowden CML 43 297 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 27 136 0 26 Feb 2021
Learning Sparse Nonparametric DAGs Xun Zheng Chen Dan Bryon Aragam Pradeep Ravikumar Eric Xing CML 119 257 0 29 Sep 2019