Causal Discovery from Temporal Data: An Overview and New Perspectives

17 March 2023

Papers citing "Causal Discovery from Temporal Data: An Overview and New Perspectives"

48 / 48 papers shown

Title
Adapt3R: Adaptive 3D Scene Representation for Domain Transfer in Imitation Learning Albert Wilcox Mohamed Ghanem Masoud Moghani Pierre Barroso Benjamin Joffe Animesh Garg 113 0 0 06 Mar 2025
Causally-informed Deep Learning towards Explainable and Generalizable Outcomes Prediction in Critical Care Yuxiao Cheng Xinxin Song Ziqian Wang Qin Zhong Kunlun He J. Suo OOD CML 107 0 0 04 Feb 2025
Cardinality-Regularized Hawkes-Granger Model T. Idé Georgios Kollias Dzung Phan Naoki Abe 85 12 0 28 Jan 2025
MotifDisco: Motif Causal Discovery For Time Series Motifs Josephine Lamp M. Derdzinski Christopher Hannemann Sam Hatfield Joost van der Linden AI4TS CML BDL 105 0 0 23 Sep 2024
GinAR: An End-To-End Multivariate Time Series Forecasting Model Suitable for Variable Missing Chengqing Yu Fei Wang Zezhi Shao Tangwen Qian Zhao Zhang Wei Wei Yongjun Xu AI4CE 85 19 0 18 May 2024
Root Cause Analysis In Microservice Using Neural Granger Causal Discovery Cheng-Ming Lin Ching Chang Wei-Yao Wang Kuang-Da Wang Wenjie Peng AI4TS 78 13 0 02 Feb 2024
Causal discovery for time series with constraint-based model and PMIME measure A. Arsac Aurore Lomet Jean-Philippe Poli CML AI4TS 13 1 0 31 May 2023
Causal Reasoning and Large Language Models: Opening a New Frontier for Causality Emre Kıcıman Robert Osazuwa Ness Amit Sharma Chenhao Tan LRM ELM 65 269 0 28 Apr 2023
CIPCaD-Bench: Continuous Industrial Process datasets for benchmarking Causal Discovery methods Giovanni Menegozzo Diego DallÁlba Paolo Fiorini 64 7 0 02 Aug 2022
Interpretable Gait Recognition by Granger Causality Michal Balazia Katerina Hlaváčková-Schindler Petr Sojka Claudia Plant CVBM 29 1 0 14 Jun 2022
A survey of Bayesian Network structure learning N. K. Kitson Anthony C. Constantinou Zhi-gao Guo Yang Liu Kiattikun Chobtham CML 45 187 0 23 Sep 2021
Active Learning of Continuous-time Bayesian Networks through Interventions Dominik Linzner Heinz Koeppl CML 26 2 0 31 May 2021
THP: Topological Hawkes Processes for Learning Causal Structure on Event Sequences Ruichu Cai Siyu Wu Jie Qiao Zhifeng Hao Keli Zhang Xi Zhang 63 22 0 23 May 2021
Granger Causality: A Review and Recent Advances Ali Shojaie E. Fox CML AI4TS 51 265 0 05 May 2021
D'ya like DAGs? A Survey on Structure Learning and Causal Discovery M. Vowels Necati Cihan Camgöz Richard Bowden CML 66 297 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 48 138 0 26 Feb 2021
Inductive Granger Causal Modeling for Multivariate Time Series Yunfei Chu Xiaowei Wang Jianxin Ma Kunyang Jia Jingren Zhou Hongxia Yang CML AI4TS 29 11 0 10 Feb 2021
Causal Inference from Slowly Varying Nonstationary Processes Kang Du Yu Xiang 80 6 0 23 Dec 2020
On the Convergence of Continuous Constrained Optimization for Structure Learning Ignavier Ng Sébastien Lachapelle Nan Rosemary Ke Simon Lacoste-Julien Kun Zhang 62 38 0 23 Nov 2020
High-recall causal discovery for autocorrelated time series with latent confounders Andreas Gerhardus J. Runge CML AI4TS 34 101 0 03 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 77 131 0 18 Jun 2020
Discovering contemporaneous and lagged causal relations in autocorrelated nonlinear time series datasets Jakob Runge 50 187 0 07 Mar 2020
Weakly-Supervised Disentanglement Without Compromises Francesco Locatello Ben Poole Gunnar Rätsch Bernhard Schölkopf Olivier Bachem Michael Tschannen CoGe OOD DRL 205 315 0 07 Feb 2020
CLEVRER: CoLlision Events for Video REpresentation and Reasoning Kexin Yi Yuta Saito Yunzhu Li Pushmeet Kohli Jiajun Wu Antonio Torralba J. Tenenbaum NAI 76 465 0 03 Oct 2019
Learning Sparse Nonparametric DAGs Xun Zheng Chen Dan Bryon Aragam Pradeep Ravikumar Eric Xing CML 140 257 0 29 Sep 2019
Attention is not not Explanation Sarah Wiegreffe Yuval Pinter XAI AAML FAtt 48 901 0 13 Aug 2019
Gradient-Based Neural DAG Learning Sébastien Lachapelle P. Brouillard T. Deleu Simon Lacoste-Julien BDL CML 45 270 0 05 Jun 2019
Exploring Interpretable LSTM Neural Networks over Multi-Variable Data Tian Guo Tao R. Lin Nino Antulov-Fantulin AI4TS 47 155 0 28 May 2019
Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models Erdun Gao Kun Zhang Biwei Huang Clark Glymour CML AI4TS 51 64 0 26 May 2019
DAG-GNN: DAG Structure Learning with Graph Neural Networks Yue Yu Jie Chen Tian Gao Mo Yu BDL CML GNN 64 481 0 22 Apr 2019
Causal Discovery from Heterogeneous/Nonstationary Data with Independent Changes Erdun Gao Kun Zhang Jiji Zhang Joseph Ramsey Ruben Sanchez-Romero Clark Glymour Bernhard Schölkopf 49 220 0 05 Mar 2019
Attention is not Explanation Sarthak Jain Byron C. Wallace FAtt 87 1,307 0 26 Feb 2019
Deep learning for time series classification: a review Hassan Ismail Fawaz Germain Forestier J. Weber L. Idoumghar Pierre-Alain Muller AI4TS AI4CE 244 2,668 0 12 Sep 2018
Towards Robust Interpretability with Self-Explaining Neural Networks David Alvarez-Melis Tommi Jaakkola MILM XAI 105 938 0 20 Jun 2018
Causal Consistency of Structural Equation Models Paul Kishan Rubenstein S. Weichwald Stephan Bongers Joris M. Mooij Dominik Janzing Moritz Grosse-Wentrup Bernhard Schölkopf CML 64 124 0 04 Jul 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 122 5,920 0 04 Mar 2017
From Deterministic ODEs to Dynamic Structural Causal Models Paul Kishan Rubenstein Stephan Bongers Bernhard Schölkopf Joris M. Mooij 58 54 0 29 Aug 2016
Causal inference using invariant prediction: identification and confidence intervals J. Peters Peter Buhlmann N. Meinshausen OOD 96 961 0 06 Jan 2015
Causal Inference by Identification of Vector Autoregressive Processes with Hidden Components Philipp Geiger Kun Zhang Biwei Huang Dominik Janzing Bernhard Schölkopf CML LLMSV 33 79 0 14 Nov 2014
Scalable Matrix-valued Kernel Learning for High-dimensional Nonlinear Multivariate Regression and Granger Causality Vikas Sindhwani H. Q. Minh A. Lozano 92 59 0 09 Aug 2014
Causal Discovery with Continuous Additive Noise Models Jonas Peters Joris Mooij Dominik Janzing Bernhard Schölkopf CML 84 563 0 26 Sep 2013
Causal interpretation of stochastic differential equations Alexander Sokol N. Hansen CML 98 50 0 31 Mar 2013
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data David Heckerman D. Geiger D. M. Chickering TPM 98 3,980 0 27 Feb 2013
Learning Equivalence Classes of Bayesian Networks Structures D. M. Chickering 75 831 0 13 Feb 2013
The Bayesian Structural EM Algorithm N. Friedman BDL TPM 145 714 0 30 Jan 2013
Learning Continuous Time Bayesian Networks Uri Nodelman C. Shelton D. Koller 127 145 0 19 Oct 2012
Learning Why Things Change: The Difference-Based Causality Learner M. Voortman D. Dash Marek J Druzdzel CML 73 41 0 15 Mar 2012
Kernel-based Conditional Independence Test and Application in Causal Discovery Kun Zhang J. Peters Dominik Janzing Bernhard Schölkopf BDL CML 82 618 0 14 Feb 2012