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Economy Statistical Recurrent Units For Inferring Nonlinear Granger Causality

22 November 2019

Saurabh Khanna

Vincent Y. F. Tan

AI4TS

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Papers citing "Economy Statistical Recurrent Units For Inferring Nonlinear Granger Causality"

45 / 45 papers shown

Title
CausalDynamics: A large-scale benchmark for structural discovery of dynamical causal models Benjamin Herdeanu Juan Nathaniel Carla Roesch Jatan Buch Gregor Ramien Johannes Haux Pierre Gentine CML AI4CE 105 0 0 22 May 2025
Adapt3R: Adaptive 3D Scene Representation for Domain Transfer in Imitation Learning Albert Wilcox Mohamed Ghanem Masoud Moghani Pierre Barroso Benjamin Joffe Animesh Garg 162 0 0 06 Mar 2025
Time Series Domain Adaptation via Latent Invariant Causal Mechanism Ruichu Cai Junxian Huang Zhenhui Yang Zijian Li Emadeldeen Eldele Min Wu Gang Hua OOD CML BDL AI4TS 110 0 0 23 Feb 2025
Causal Temporal Regime Structure Learning Abdellah Rahmani Pascal Frossard CML 256 2 0 20 Feb 2025
GCAD: Anomaly Detection in Multivariate Time Series from the Perspective of Granger Causality Zehao Liu Mengzhou Gao Pengfei Jiao CML AI4TS 93 3 0 23 Jan 2025
LinBridge: A Learnable Framework for Interpreting Nonlinear Neural Encoding Models Xiaohui Gao Yue Cheng Peiyang Li Yijie Niu Yifan Ren Yiheng Liu Haiyang Sun Zhuoyi Li Weiwei Xing Xintao Hu AI4CE 48 0 0 26 Oct 2024
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 151 0 0 25 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 82 0 0 15 Aug 2024
CausalMMM: Learning Causal Structure for Marketing Mix Modeling Chang Gong Di Yao Lei Zhang Sheng Chen Wenbin Li Yueyang Su Jingping Bi 81 6 0 24 Jun 2024
Learning Flexible Time-windowed Granger Causality Integrating Heterogeneous Interventional Time Series Data Ziyi Zhang Shaogang Ren Xiaoning Qian Nick Duffield AI4TS CML 69 3 0 14 Jun 2024
Jacobian Regularizer-based Neural Granger Causality Wanqi Zhou Shuanghao Bai Shujian Yu Qibin Zhao Badong Chen CML 85 4 0 14 May 2024
CASPER: Causality-Aware Spatiotemporal Graph Neural Networks for Spatiotemporal Time Series Imputation Baoyu Jing Dawei Zhou Kan Ren Carl Yang CML AI4TS 103 10 0 18 Mar 2024
A VAE-based Framework for Learning Multi-Level Neural Granger-Causal Connectivity Jiahe Lin Huitian Lei G. Michailidis CML 113 0 0 25 Feb 2024
Bayesian Vector AutoRegression with Factorised Granger-Causal Graphs He Zhao V. Kitsios Terry O'Kane Edwin V. Bonilla CML 105 1 0 06 Feb 2024
Doubly Robust Structure Identification from Temporal Data Emmanouil Angelis Francesco Quinzan Ashkan Soleymani Patrick Jaillet Stefan Bauer CML OOD 78 2 0 10 Nov 2023
Neural Structure Learning with Stochastic Differential Equations Benjie Wang Joel Jennings Wenbo Gong CML AI4TS 66 7 0 06 Nov 2023
Discovering Mixtures of Structural Causal Models from Time Series Data Sumanth Varambally Yi-An Ma Rose Yu 112 6 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 91 17 0 03 Oct 2023
Interpretable Imitation Learning with Dynamic Causal Relations ianxiang Zhao Wenchao Yu Suhang Wang Lu Wang Xiang Zhang Yuncong Chen Yanchi Liu Wei Cheng Haifeng Chen CML 59 2 0 30 Sep 2023
Nonlinear Permuted Granger Causality Noah D. Gade J. Rodu CML 70 0 0 11 Aug 2023
Discovering Causality for Efficient Cooperation in Multi-Agent Environments Rafael Pina V. D. Silva Corentin Artaud 64 4 0 20 Jun 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 99 26 0 10 May 2023
Collective Relational Inference for learning heterogeneous interactions Zhichao Han Olga Fink David S. Kammer 71 1 0 30 Apr 2023
Causal Discovery from Temporal Data: An Overview and New Perspectives Chang Gong Di Yao Chuzhe Zhang Wenbin Li Jingping Bi AI4TS CML 114 18 0 17 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 76 28 0 15 Feb 2023
Deep Causal Learning: Representation, Discovery and Inference Zizhen Deng Xiaolong Zheng Hu Tian D. Zeng CML BDL 119 11 0 07 Nov 2022
Rhino: Deep Causal Temporal Relationship Learning With History-dependent Noise Wenbo Gong Joel Jennings Chen Zhang Nick Pawlowski AI4TS CML 92 27 0 26 Oct 2022
Granger causal inference on DAGs identifies genomic loci regulating transcription Rohit Singh Alexander P. Wu Bonnie Berger CML 69 17 0 18 Oct 2022
GLACIAL: Granger and Learning-based Causality Analysis for Longitudinal Studies Minh Le Nguyen G. Ngo M. Sabuncu CML 26 2 0 13 Oct 2022
Learning domain-specific causal discovery from time series Xinyue Wang Konrad Paul Kording BDL CML AI4TS 52 1 0 12 Sep 2022
Jacobian Granger Causal Neural Networks for Analysis of Stationary and Nonstationary Data Suryadi Yew-Soon Ong Lock Yue Chew CML 24 0 0 19 May 2022
Bayesian Spillover Graphs for Dynamic Networks Grace Deng David S. Matteson 72 3 0 03 Mar 2022
Deep Recurrent Modelling of Granger Causality with Latent Confounding Zexuan Yin P. Barucca CML BDL 50 13 0 23 Feb 2022
NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge Xiangyuan Sun Oliver Schulte Guiliang Liu Pascal Poupart CML BDL 105 22 0 09 Sep 2021
Learning interaction rules from multi-animal trajectories via augmented behavioral models Keisuke Fujii Naoya Takeishi Kazushi Tsutsui Emyo Fujioka Nozomi Nishiumi ... Hiroyoshi Kohno K. Yoda S. Takahashi S. Hiryu Yoshinobu Kawahara 75 13 0 12 Jul 2021
An Interpretable Neural Network for Parameter Inference Johann Pfitzinger 69 0 0 10 Jun 2021
Causal Graph Discovery from Self and Mutually Exciting Time Series S. Wei Yao Xie C. Josef Rishikesan Kamaleswaran CML 89 2 0 04 Jun 2021
Neural graphical modelling in continuous-time: consistency guarantees and algorithms Alexis Bellot K. Branson M. Schaar CML AI4TS 93 46 0 06 May 2021
Causal Inference for Time series Analysis: Problems, Methods and Evaluation Raha Moraffah Paras Sheth Mansooreh Karami Anchit Bhattacharya Qianru Wang Anique Tahir A. Raglin Huan Liu CML AI4TS 113 110 0 11 Feb 2021
Interpretable Models for Granger Causality Using Self-explaining Neural Networks Ricards Marcinkevics Julia E. Vogt MILM CML 91 64 0 19 Jan 2021
Interpretability and Explainability: A Machine Learning Zoo Mini-tour Ricards Marcinkevics Julia E. Vogt XAI 90 121 0 03 Dec 2020
Discovering long term dependencies in noisy time series data using deep learning A. Kurochkin AI4TS 34 0 0 15 Nov 2020
Neural Additive Vector Autoregression Models for Causal Discovery in Time Series Bart Bussmann Jannes Nys Steven Latré CML BDL 60 26 0 19 Oct 2020
Decentralized policy learning with partial observation and mechanical constraints for multiperson modeling Keisuke Fujii Naoya Takeishi Yoshinobu Kawahara K. Takeda 68 9 0 07 Jul 2020
Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data Sindy Löwe David Madras R. Zemel Max Welling CML BDL AI4TS 129 133 0 18 Jun 2020