ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2003.03685
  4. Cited By
Discovering contemporaneous and lagged causal relations in
  autocorrelated nonlinear time series datasets
v1v2 (latest)

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

7 March 2020
Jakob Runge
ArXiv (abs)PDFHTML

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

26 / 76 papers shown
Title
A Survey on Causal Discovery Methods for I.I.D. and Time Series Data
A Survey on Causal Discovery Methods for I.I.D. and Time Series Data
Uzma Hasan
Emam Hossain
Md. Osman Gani
CMLAI4TS
126
31
0
27 Mar 2023
Causal Discovery from Temporal Data: An Overview and New Perspectives
Causal Discovery from Temporal Data: An Overview and New Perspectives
Chang Gong
Di Yao
Chuzhe Zhang
Wenbin Li
Jingping Bi
AI4TSCML
114
18
0
17 Mar 2023
Causal Temporal Graph Convolutional Neural Networks (CTGCN)
Causal Temporal Graph Convolutional Neural Networks (CTGCN)
Abigail Langbridge
Fearghal O'Donncha
Amadou Ba
Fabio Lorenzi
Christopher Lohse
J. Ploennigs
GNN
46
1
0
16 Mar 2023
Root Cause Identification for Collective Anomalies in Time Series given
  an Acyclic Summary Causal Graph with Loops
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
45
21
0
07 Mar 2023
eCDANs: Efficient Temporal Causal Discovery from Autocorrelated and
  Non-stationary Data (Student Abstract)
eCDANs: Efficient Temporal Causal Discovery from Autocorrelated and Non-stationary Data (Student Abstract)
Muhammad Hasan Ferdous
Uzma Hasan
Md. Osman Gani
67
2
0
06 Mar 2023
Enhancing Causal Discovery from Robot Sensor Data in Dynamic Scenarios
Enhancing Causal Discovery from Robot Sensor Data in Dynamic Scenarios
Luca Castri
Sariah Mghames
Marc Hanheide
Nicola Bellotto
CML
75
13
0
20 Feb 2023
CDANs: Temporal Causal Discovery from Autocorrelated and Non-Stationary
  Time Series Data
CDANs: Temporal Causal Discovery from Autocorrelated and Non-Stationary Time Series Data
Muhammad Hasan Ferdous
Uzma Hasan
Md. Osman Gani
CML
64
3
0
07 Feb 2023
Hierarchical Graph Neural Networks for Causal Discovery and Root Cause
  Localization
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
57
19
0
03 Feb 2023
GDBN: a Graph Neural Network Approach to Dynamic Bayesian Network
GDBN: a Graph Neural Network Approach to Dynamic Bayesian Network
Yang Sun
Yifan Xie
BDLCML
119
1
0
28 Jan 2023
Sensor data-driven analysis for identification of causal relationships
  between exposure to air pollution and respiratory rate in asthmatics
Sensor data-driven analysis for identification of causal relationships between exposure to air pollution and respiratory rate in asthmatics
D. Arvind
S. Maiya
51
1
0
16 Jan 2023
Rhino: Deep Causal Temporal Relationship Learning With History-dependent
  Noise
Rhino: Deep Causal Temporal Relationship Learning With History-dependent Noise
Wenbo Gong
Joel Jennings
Chen Zhang
Nick Pawlowski
AI4TSCML
92
27
0
26 Oct 2022
GLACIAL: Granger and Learning-based Causality Analysis for Longitudinal
  Studies
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
Learning domain-specific causal discovery from time series
Xinyue Wang
Konrad Paul Kording
BDLCMLAI4TS
52
1
0
12 Sep 2022
Causal discovery for time series with latent confounders
Causal discovery for time series with latent confounders
Christian Reiser
BDLCMLAI4TS
37
4
0
07 Sep 2022
Multiscale Causal Structure Learning
Multiscale Causal Structure Learning
Gabriele DÁcunto
P. Lorenzo
Sergio Barbarossa
98
7
0
16 Jul 2022
Causal Discovery using Model Invariance through Knockoff Interventions
Causal Discovery using Model Invariance through Knockoff Interventions
Wasim Ahmad
M. Shadaydeh
Joachim Denzler
CML
57
4
0
08 Jul 2022
A Causal Research Pipeline and Tutorial for Psychologists and Social
  Scientists
A Causal Research Pipeline and Tutorial for Psychologists and Social Scientists
M. Vowels
CML
76
2
0
10 Jun 2022
Inferring extended summary causal graphs from observational time series
Inferring extended summary causal graphs from observational time series
Charles K. Assaad
Emilie Devijver
Éric Gaussier
CMLAI4TS
16
0
0
19 May 2022
Achieving Long-Term Fairness in Sequential Decision Making
Achieving Long-Term Fairness in Sequential Decision Making
Yaowei Hu
Lu Zhang
72
22
0
04 Apr 2022
Causal de Finetti: On the Identification of Invariant Causal Structure
  in Exchangeable Data
Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data
Siyuan Guo
V. Tóth
Bernhard Schölkopf
Ferenc Huszár
CML
94
37
0
29 Mar 2022
Path Signature Area-Based Causal Discovery in Coupled Time Series
Path Signature Area-Based Causal Discovery in Coupled Time Series
William E. Glad
T. Woolf
CML
164
3
0
23 Oct 2021
NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge
NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge
Xiangyuan Sun
Oliver Schulte
Guiliang Liu
Pascal Poupart
CMLBDL
105
22
0
09 Sep 2021
Interactive Causal Structure Discovery in Earth System Sciences
Interactive Causal Structure Discovery in Earth System Sciences
Laila Melkas
Rafael Savvides
Suyog H. Chandramouli
J. Mäkelä
T. Nieminen
I. Mammarella
Kai Puolamäki
CML
113
6
0
01 Jul 2021
Data Generating Process to Evaluate Causal Discovery Techniques for Time
  Series Data
Data Generating Process to Evaluate Causal Discovery Techniques for Time Series Data
A. Lawrence
Marcus Kaiser
Rui Sampaio
Maksim Sipos
CMLAI4TS
109
20
0
16 Apr 2021
Causal Inference for Time series Analysis: Problems, Methods and
  Evaluation
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
CMLAI4TS
113
110
0
11 Feb 2021
High-recall causal discovery for autocorrelated time series with latent
  confounders
High-recall causal discovery for autocorrelated time series with latent confounders
Andreas Gerhardus
J. Runge
CMLAI4TS
107
102
0
03 Jul 2020
Previous
12