Learning Networks of Stochastic Differential Equations

1 November 2010

Papers citing "Learning Networks of Stochastic Differential Equations"

38 / 38 papers shown

Title
Ergodic Network Stochastic Differential Equations F. Iafrate S. Iacus 34 0 0 23 Dec 2024
Signed-Perturbed Sums Estimation of ARX Systems: Exact Coverage and Strong Consistency (Extended Version) A. Carè E. Weyer Balázs Cs. Csáji M. Campi 20 0 0 18 Feb 2024
Squared Wasserstein-2 Distance for Efficient Reconstruction of Stochastic Differential Equations Mingtao Xia Xiangting Li Qijing Shen Tom Chou 11 4 0 21 Jan 2024
Inferring the Graph of Networked Dynamical Systems under Partial Observability and Spatially Colored Noise Augusto Santos Diogo Rente Rui Seabra José M. F. Moura 18 1 0 18 Dec 2023
Learning the Causal Structure of Networked Dynamical Systems under Latent Nodes and Structured Noise Augusto Santos Diogo Rente Rui Seabra José M. F. Moura 19 4 0 10 Dec 2023
Learning linear dynamical systems under convex constraints Hemant Tyagi D. Efimov 13 1 0 27 Mar 2023
Learning Transition Operators From Sparse Space-Time Samples C. Kümmerle Mauro Maggioni Sui Tang 26 1 0 01 Dec 2022
Recovering the Graph Underlying Networked Dynamical Systems under Partial Observability: A Deep Learning Approach Sérgio Machado Anirudh Sridhar P. Gil J. Henriques J. M. F. Moura A. Santos CML 12 2 0 08 Aug 2022
Parabolic Relaxation for Quadratically-constrained Quadratic Programming -- Part II: Theoretical & Computational Results Ramtin Madani Mersedeh Ashraphijuo Mohsen Kheirandishfard Alper Atamtürk 11 3 0 07 Aug 2022
Efficient and passive learning of networked dynamical systems driven by non-white exogenous inputs Harish Doddi Deepjyoti Deka Saurav Talukdar M. Salapaka 34 6 0 02 Oct 2021
Neural graphical modelling in continuous-time: consistency guarantees and algorithms Alexis Bellot K. Branson M. Schaar CML AI4TS 24 43 0 06 May 2021
Which Neural Network to Choose for Post-Fault Localization, Dynamic State Estimation and Optimal Measurement Placement in Power Systems? A. Afonin Michael Chertkov 17 3 0 07 Apr 2021
Sticky PDMP samplers for sparse and local inference problems J. Bierkens Sebastiano Grazzi Frank van der Meulen Moritz Schauer 11 15 0 15 Mar 2021
Online Stochastic Gradient Descent Learns Linear Dynamical Systems from A Single Trajectory Navid Reyhanian Jarvis Haupt 21 3 0 23 Feb 2021
High-Dimensional Dynamic Systems Identification with Additional Constraints Junlin Li 19 0 0 20 Dec 2019
Efficient Learning of Distributed Linear-Quadratic Controllers S. Fattahi Nikolai Matni Somayeh Sojoudi 11 9 0 21 Sep 2019
Robust Guarantees for Perception-Based Control Sarah Dean Nikolai Matni Benjamin Recht Vickie Ye 14 79 0 08 Jul 2019
Learning Sparse Dynamical Systems from a Single Sample Trajectory S. Fattahi Nikolai Matni Somayeh Sojoudi 18 40 0 20 Apr 2019
Physics Informed Topology Learning in Networks of Linear Dynamical Systems Saurav Talukdar Deepjyoti Deka Harish Doddi D. Materassi Michael Chertkov M. Salapaka AI4CE 16 22 0 27 Sep 2018
Stochastic Gradient Descent Learns State Equations with Nonlinear Activations Samet Oymak 13 43 0 09 Sep 2018
Non-asymptotic Identification of LTI Systems from a Single Trajectory Samet Oymak N. Ozay 16 221 0 14 Jun 2018
Sample Complexity of Sparse System Identification Problem S. Fattahi Somayeh Sojoudi 16 12 0 21 Mar 2018
Online Learning of Power Transmission Dynamics A. Lokhov Marc Vuffray Dmitry Shemetov Deepjyoti Deka Michael Chertkov 25 24 0 27 Oct 2017
On the Sample Complexity of the Linear Quadratic Regulator Sarah Dean Horia Mania Nikolai Matni Benjamin Recht Stephen Tu 40 569 0 04 Oct 2017
On the Sample Complexity of Graphical Model Selection for Non-Stationary Processes Nguyen Tran Quang Oleksii Abramenko A. Jung 19 4 0 17 Jan 2017
Mixing Times and Structural Inference for Bernoulli Autoregressive Processes Dimitrios Katselis Carolyn L. Beck R. Srikant 24 14 0 19 Dec 2016
Learning conditional independence structure for high-dimensional uncorrelated vector processes Nguyen Tran Quang A. Jung 15 7 0 13 Sep 2016
Reconstructing undirected graphs from eigenspaces Yohann De Castro T. Espinasse Paul Rochet 18 8 0 26 Mar 2016
Graphical LASSO Based Model Selection for Time Series A. Jung Gabor Hannak N. Goertz 26 64 0 05 Oct 2014
Learning the Conditional Independence Structure of Stationary Time Series: A Multitask Learning Approach A. Jung 39 31 0 04 Apr 2014
On the Information-theoretic Limits of Graphical Model Selection for Gaussian Time Series Gabor Hannak A. Jung N. Goertz 31 6 0 04 Mar 2014
Compressive Nonparametric Graphical Model Selection For Time Series A. Jung Reinhard Heckel Helmut Bölcskei F. Hlawatsch CML 51 18 0 13 Nov 2013
Support Recovery for the Drift Coefficient of High-Dimensional Diffusions José Bento M. Ibrahimi 32 6 0 19 Aug 2013
A Direct Estimation of High Dimensional Stationary Vector Autoregressions Fang Han Huanran Lu Han Liu 66 120 0 01 Jul 2013
Efficient Reinforcement Learning for High Dimensional Linear Quadratic Systems M. Ibrahimi Adel Javanmard Benjamin Van Roy 36 91 0 24 Mar 2013
Learning the Dependence Graph of Time Series with Latent Factors A. Jalali Sujay Sanghavi CML 57 44 0 09 Jun 2011
Causal Network Inference via Group Sparse Regularization Andrew K. Bolstad B. V. Veen Robert D. Nowak CML 51 142 0 03 Jun 2011
Information Theoretic Limits on Learning Stochastic Differential Equations José Bento M. Ibrahimi Andrea Montanari 61 8 0 09 Mar 2011