Discovering contemporaneous and lagged causal relations in autocorrelated nonlinear time series datasets

7 March 2020

Papers citing "Discovering contemporaneous and lagged causal relations in autocorrelated nonlinear time series datasets"

50 / 73 papers shown

Title
Deep Koopman operator framework for causal discovery in nonlinear dynamical systems Juan Nathaniel Carla Roesch Jatan Buch Derek DeSantis Adam Rupe Kara Lamb Pierre Gentine CML 14 0 0 20 May 2025
Causality-enhanced Decision-Making for Autonomous Mobile Robots in Dynamic Environments Luca Castri Gloria Beraldo Nicola Bellotto 46 0 0 16 Apr 2025
An Asymmetric Independence Model for Causal Discovery on Path Spaces Georg Manten Cecilia Casolo Søren Wengel Mogensen Niki Kilbertus 68 0 0 12 Mar 2025
Adapt3R: Adaptive 3D Scene Representation for Domain Transfer in Imitation Learning Albert Wilcox Mohamed Ghanem Masoud Moghani Pierre Barroso Benjamin Joffe Animesh Garg 52 0 0 06 Mar 2025
Correlation to Causation: A Causal Deep Learning Framework for Arctic Sea Ice Prediction Emam Hossain Muhammad Hasan Ferdous Jianwu Wang Aneesh Subramanian Md. Osman Gani OOD CML AI4CE 81 0 0 03 Mar 2025
Causal Temporal Regime Structure Learning Abdellah Rahmani Pascal Frossard CML 93 2 0 20 Feb 2025
Identification of Nonparametric Dynamic Causal Structure and Latent Process in Climate System Minghao Fu Zhen Zhang Zijian Li Yujia Zheng Ignavier Ng Yingyao Hu Kun Zhang CML 55 0 0 21 Jan 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
Scalable Temporal Anomaly Causality Discovery in Large Systems: Achieving Computational Efficiency with Binary Anomaly Flag Data M. Asres C. Omlin the CMS-HCAL Collaboration 83 0 0 16 Dec 2024
CausalStock: Deep End-to-end Causal Discovery for News-driven Stock Movement Prediction Shuqi Li Yuebo Sun Yuxin Lin Xin Gao Shuo Shang Rui Yan AIFin 31 1 0 10 Nov 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 37 3 0 09 Oct 2024
CAnDOIT: Causal Discovery with Observational and Interventional Data from Time-Series Luca Castri Sariah Mghames Marc Hanheide Nicola Bellotto CML 26 1 0 03 Oct 2024
Causal Discovery from Time-Series Data with Short-Term Invariance-Based Convolutional Neural Networks Rujia Shen Boran Wang Chao Zhao Yi Guan Jingchi Jiang CML BDL AI4TS 34 0 0 15 Aug 2024
Sortability of Time Series Data Christopher Lohse Jonas Wahl CML 47 1 0 18 Jul 2024
XTraffic: A Dataset Where Traffic Meets Incidents with Explainability and More Xiaochuan Gou Ziyue Li Tian-Shing Lan Junpeng Lin Zhishuai Li Bingyu Zhao Chen Zhang Di Wang Xiangliang Zhang AI4TS 62 1 0 16 Jul 2024
Learning Dynamic Bayesian Networks from Data: Foundations, First Principles and Numerical Comparisons Vyacheslav Kungurtsev Fadwa Idlahcen Petr Rysavý Pavel Rytír Ales Wodecki 54 1 0 25 Jun 2024
Experimental Evaluation of ROS-Causal in Real-World Human-Robot Spatial Interaction Scenarios Luca Castri Gloria Beraldo Sariah Mghames Marc Hanheide Nicola Bellotto 48 3 0 07 Jun 2024
RealTCD: Temporal Causal Discovery from Interventional Data with Large Language Model Peiwen Li Xin Wang Zeyang Zhang Yuan Meng Fang-lin Shen Yue Li Jialong Wang Yang Li Wenweu Zhu 56 3 0 23 Apr 2024
The Causal Chambers: Real Physical Systems as a Testbed for AI Methodology Juan L. Gamella Jonas Peters Peter Buhlmann 84 8 0 17 Apr 2024
TS-CausalNN: Learning Temporal Causal Relations from Non-linear Non-stationary Time Series Data Omar Faruque Sahara Ali Xue Zheng Jianwu Wang AI4TS BDL CML 60 1 0 01 Apr 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 51 8 0 28 Feb 2024
ROS-Causal: A ROS-based Causal Analysis Framework for Human-Robot Interaction Applications Luca Castri Gloria Beraldo Sariah Mghames Marc Hanheide Nicola Bellotto 31 4 0 25 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
Bayesian Vector AutoRegression with Factorised Granger-Causal Graphs He Zhao V. Kitsios Terry O'Kane Edwin V. Bonilla CML 24 1 0 06 Feb 2024
Long-Term Fair Decision Making through Deep Generative Models Yaowei Hu Yongkai Wu Lu Zhang FaML 32 1 0 20 Jan 2024
Towards Causal Representations of Climate Model Data Julien Boussard Chandni Nagda Julia Kaltenborn C. E. E. Lange Philippe Brouillard Yaniv Gurwicz Peer Nowack David Rolnick 22 4 0 05 Dec 2023
Doubly Robust Structure Identification from Temporal Data Emmanouil Angelis Francesco Quinzan Ashkan Soleymani Patrick Jaillet Stefan Bauer CML OOD 37 2 0 10 Nov 2023
Neural Structure Learning with Stochastic Differential Equations Benjie Wang Joel Jennings Wenbo Gong CML AI4TS 28 3 0 06 Nov 2023
A Review and Roadmap of Deep Causal Model from Different Causal Structures and Representations Hang Chen Keqing Du Chenguang Li Xinyu Yang 54 2 0 02 Nov 2023
Causal Feature Selection via Transfer Entropy Paolo Bonetti Alberto Maria Metelli Marcello Restelli CML 18 6 0 17 Oct 2023
Discovering Mixtures of Structural Causal Models from Time Series Data Sumanth Varambally Yi Ma Rose Yu 24 5 0 10 Oct 2023
Projecting infinite time series graphs to finite marginal graphs using number theory Andreas Gerhardus Jonas Wahl Sofia Faltenbacher Urmi Ninad Jakob Runge AI4TS 28 3 0 09 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 32 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
TNPAR: Topological Neural Poisson Auto-Regressive Model for Learning Granger Causal Structure from Event Sequences Yuequn Liu Ruichu Cai Wei Chen Jie Qiao Yuguang Yan Zijian Li Keli Zhang Zhifeng Hao CML 23 4 0 25 Jun 2023
Bootstrap aggregation and confidence measures to improve time series causal discovery Kevin Debeire Jakob Runge Andreas Gerhardus Berlin CML AI4TS 12 7 0 15 Jun 2023
Causal Discovery from Time Series with Hybrids of Constraint-Based and Noise-Based Algorithms D. Bystrova Charles K. Assaad Julyan Arbel Emilie Devijver Éric Gaussier W. Thuiller AI4TS CML 32 6 0 14 Jun 2023
Foundations of Causal Discovery on Groups of Variables Jonas Wahl Urmi Ninad Jakob Runge CML 14 9 0 12 Jun 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
Disentangled Causal Graph Learning for Online Unsupervised Root Cause Analysis Dongjie Wang Zhengzhang Chen Yanjie Fu Yanchi Liu Haifeng Chen CML 27 0 0 18 May 2023
Structural Hawkes Processes for Learning Causal Structure from Discrete-Time Event Sequences Jie Qiao Ruichu Cai Siyu Wu Yu Xiang Keli Zhang Zhifeng Hao CML AI4TS 33 5 0 10 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
Causal Discovery with Stage Variables for Health Time Series Bharat Srikishan Samantha Kleinberg CML 22 0 0 05 May 2023
Selecting Robust Features for Machine Learning Applications using Multidata Causal Discovery S. SaranyaGanesh Tom Beucler Frederick Iat-Hin Tam Milton S. Gomez Jakob Runge Andreas Gerhardus 20 4 0 11 Apr 2023
AI for IT Operations (AIOps) on Cloud Platforms: Reviews, Opportunities and Challenges Qian Cheng Doyen Sahoo Amrita Saha Wenjing Yang Chenghao Liu Gerald Woo Manpreet Singh Silvio Saverese Guosheng Lin 48 18 0 10 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 42 24 0 27 Mar 2023
Causal Discovery from Temporal Data: An Overview and New Perspectives Chang Gong Di Yao Chuzhe Zhang Wenbin Li Jingping Bi AI4TS CML 21 17 0 17 Mar 2023
Causal Temporal Graph Convolutional Neural Networks (CTGCN) Abigail Langbridge Fearghal O'Donncha Amadou Ba Fabio Lorenzi Christopher Lohse J. Ploennigs GNN 22 1 0 16 Mar 2023
Root Cause Identification for Collective Anomalies in Time Series given an Acyclic Summary Causal Graph with Loops Charles K. Assaad Imad Ez-zejjari Lei Zan AI4TS 13 18 0 07 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