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. 1912.10829
  4. Cited By
Variable-lag Granger Causality for Time Series Analysis

Variable-lag Granger Causality for Time Series Analysis

18 December 2019
Chainarong Amornbunchornvej
Elena Zheleva
T. Berger-Wolf
    CML
    AI4TS
ArXivPDFHTML

Papers citing "Variable-lag Granger Causality for Time Series Analysis"

11 / 11 papers shown
Title
Causal Temporal Regime Structure Learning
Causal Temporal Regime Structure Learning
Abdellah Rahmani
Pascal Frossard
CML
193
2
0
20 Feb 2025
Beyond Predictions in Neural ODEs: Identification and Interventions
Beyond Predictions in Neural ODEs: Identification and Interventions
H. Aliee
Fabian J. Theis
Niki Kilbertus
CML
84
24
0
23 Jun 2021
Granger-causal Attentive Mixtures of Experts: Learning Important
  Features with Neural Networks
Granger-causal Attentive Mixtures of Experts: Learning Important Features with Neural Networks
Patrick Schwab
Djordje Miladinovic
W. Karlen
CML
48
57
0
06 Feb 2018
Coordination Event Detection and Initiator Identification in Time Series
  Data
Coordination Event Detection and Initiator Identification in Time Series Data
Chainarong Amornbunchornvej
Ivan Brugere
Ariana Strandburg-Peshkin
D. Farine
M. Crofoot
T. Berger-Wolf
AI4TS
36
22
0
04 Mar 2016
Granger Causality in Multi-variate Time Series using a Time Ordered
  Restricted Vector Autoregressive Model
Granger Causality in Multi-variate Time Series using a Time Ordered Restricted Vector Autoregressive Model
Elsa Siggiridou
D. Kugiumtzis
CML
49
98
0
11 Nov 2015
Telling cause from effect in deterministic linear dynamical systems
Telling cause from effect in deterministic linear dynamical systems
Naji Shajarisales
Dominik Janzing
Bernhard Schölkopf
M. Besserve
AI4TS
CML
60
50
0
04 Mar 2015
On Causal and Anticausal Learning
On Causal and Anticausal Learning
Bernhard Schölkopf
Dominik Janzing
J. Peters
Eleni Sgouritsa
Kun Zhang
Joris Mooij
CML
81
607
0
27 Jun 2012
Sparse-GEV: Sparse Latent Space Model for Multivariate Extreme Value
  Time Serie Modeling
Sparse-GEV: Sparse Latent Space Model for Multivariate Extreme Value Time Serie Modeling
Yan Liu
M. T. Bahadori
Hongfei Li
AI4TS
68
33
0
18 Jun 2012
Directed Information Graphs
Directed Information Graphs
Christopher J. Quinn
Negar Kiyavash
Todd P. Coleman
CML
107
148
0
09 Apr 2012
The Total s-Energy of a Multiagent System
The Total s-Energy of a Multiagent System
Bernard Chazelle
101
95
0
09 Apr 2010
Causal inference using the algorithmic Markov condition
Causal inference using the algorithmic Markov condition
Dominik Janzing
Bernhard Schölkopf
CML
133
306
0
23 Apr 2008
1