Causal Network Inference via Group Sparse Regularization

3 June 2011

Papers citing "Causal Network Inference via Group Sparse Regularization"

34 / 34 papers shown

Title
Time-Varying Graph Learning for Data with Heavy-Tailed Distribution A. Javaheri Jiaxi Ying Daniel P. Palomar F. Marvasti 64 0 0 03 Jan 2025
Spatiotemporal Forecasting Meets Efficiency: Causal Graph Process Neural Networks Aref Einizade Fragkiskos D. Malliaros Jhony H. Giraldo AI4TS 62 1 0 29 May 2024
Estimation of a Causal Directed Acyclic Graph Process using Non-Gaussianity A. Einizade S. H. Sardouie CML 99 0 0 24 Nov 2022
Sparsity in Continuous-Depth Neural Networks H. Aliee Till Richter Mikhail Solonin I. Ibarra Fabian J. Theis Niki Kilbertus 97 11 0 26 Oct 2022
Granger Causal Chain Discovery for Sepsis-Associated Derangements via Continuous-Time Hawkes Processes S. Wei Yao Xie C. Josef Rishikesan Kamaleswaran 120 10 0 09 Sep 2022
Local Topology Inference of Mobile Robotic Networks under Formation Control Yushan Li Jianping He Lin Cai X. Guan 35 8 0 30 Apr 2022
Online Graph Topology Learning from Matrix-valued Time Series Yiye Jiang Jérémie Bigot Sofian Maabout AI4TS 53 3 0 16 Jul 2021
A scalable multi-step least squares method for network identification with unknown disturbance topology S. Fonken K. R. Ramaswamy P. V. D. Hof 11 10 0 14 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
Topology Inference for Network Systems: Causality Perspective and Non-asymptotic Performance Yushan Li Jianping He Cailian Chen X. Guan 107 5 0 02 Jun 2021
FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecasting Boris N. Oreshkin A. Amini Lucy Coyle Mark Coates AI4TS 113 101 0 30 Jul 2020
Learning sparse linear dynamic networks in a hyper-parameter free setting Arun Venkitaraman H. Hjalmarsson B. Wahlberg 29 2 0 26 Nov 2019
Economy Statistical Recurrent Units For Inferring Nonlinear Granger Causality Saurabh Khanna Vincent Y. F. Tan AI4TS 92 72 0 22 Nov 2019
Graph Topological Aspects of Granger Causal Network Learning R. Kinnear Ravi R. Mazumdar CML 54 0 0 17 Nov 2019
Localizing Changes in High-Dimensional Vector Autoregressive Processes Daren Wang Yi Yu Alessandro Rinaldo Rebecca Willett 85 22 0 12 Sep 2019
Blind identification of stochastic block models from dynamical observations Michael T. Schaub Santiago Segarra J. Tsitsiklis 47 34 0 22 May 2019
Online Topology Identification from Vector Autoregressive Time Series Bakht Zaman Luis Miguel Lopez Ramos Daniel Romero B. Beferull-Lozano 97 41 0 03 Apr 2019
Single Index Latent Variable Models for Network Topology Inference Jonathan Mei José M. F. Moura 49 0 0 28 Jun 2018
EigenNetworks Jonathan Mei J. M. F. Moura AI4TS 34 0 0 05 Jun 2018
Learning graphs from data: A signal representation perspective Xiaowen Dong D. Thanou Michael G. Rabbat P. Frossard 134 381 0 03 Jun 2018
Latent Variable Time-varying Network Inference Federico Tomasi Veronica Tozzo Saverio Salzo A. Verri CML 47 21 0 12 Feb 2018
SILVar: Single Index Latent Variable Models Jonathan Mei José M. F. Moura 96 24 0 09 May 2017
On the Sample Complexity of Graphical Model Selection for Non-Stationary Processes Nguyen Tran Quang Oleksii Abramenko A. Jung 149 4 0 17 Jan 2017
Mixing Times and Structural Inference for Bernoulli Autoregressive Processes Dimitrios Katselis Carolyn L. Beck R. Srikant 58 15 0 19 Dec 2016
Learning conditional independence structure for high-dimensional uncorrelated vector processes Nguyen Tran Quang A. Jung 107 7 0 13 Sep 2016
Validity of time reversal for testing Granger causality I. Winkler Danny Panknin Daniel Bartz K. Müller Stefan Haufe 50 58 0 25 Sep 2015
Signal Processing on Graphs: Causal Modeling of Unstructured Data Jonathan Mei José M. F. Moura CML AI4TS 154 192 0 28 Feb 2015
Joint Association Graph Screening and Decomposition for Large-scale Linear Dynamical Systems Yiyuan She Yuejia He Shijie Li D. Wu 58 6 0 17 Nov 2014
Graphical LASSO Based Model Selection for Time Series A. Jung Gabor Hannak N. Goertz 156 63 0 05 Oct 2014
Learning the Conditional Independence Structure of Stationary Time Series: A Multitask Learning Approach A. Jung 106 31 0 04 Apr 2014
Compressive Nonparametric Graphical Model Selection For Time Series A. Jung Reinhard Heckel Helmut Bölcskei F. Hlawatsch CML 95 18 0 13 Nov 2013
Conditioning of Random Block Subdictionaries with Applications to Block-Sparse Recovery and Regression W. Bajwa Marco F. Duarte A. Calderbank 91 21 0 20 Sep 2013
Support Recovery for the Drift Coefficient of High-Dimensional Diffusions José Bento M. Ibrahimi 59 6 0 19 Aug 2013
Directed Information Graphs Christopher J. Quinn Negar Kiyavash Todd P. Coleman CML 129 148 0 09 Apr 2012