State-space systems as dynamic generative models

State-space systems as dynamic generative models

Proceedings of the Royal Society A (Proc. R. Soc. A), 2024

13 March 2025

Juan-Pablo Ortega

Florian Rossmannek

ArXiv (abs)PDF HTML

Papers citing "State-space systems as dynamic generative models"

14 / 14 papers shown

Title
Echoes of the past: A unified perspective on fading memory and echo states Juan-Pablo Ortega Florian Rossmannek 96 2 0 26 Aug 2025
Stochastic dynamics learning with state-space systems Juan-Pablo Ortega Florian Rossmannek 108 1 0 11 Aug 2025
A Brief Survey on the Approximation Theory for Sequence ModellingJournal of Machine Learning (JML), 2023 Hao Jiang Qianxiao Li Zhong Li Shida Wang AI4TS 220 14 0 27 Feb 2023
Transport in reservoir computing G. Manjunath Juan-Pablo Ortega 156 6 0 16 Sep 2022
Learning strange attractors with reservoir systems Lyudmila Grigoryeva Allen G. Hart Juan-Pablo Ortega 185 31 0 11 Aug 2021
Embedding Information onto a Dynamical System G. Manjunath 318 15 0 22 May 2021
Using Data Assimilation to Train a Hybrid Forecast System that Combines Machine-Learning and Knowledge-Based ComponentsChaos (Chaos), 2021 Alexander Wikner Jaideep Pathak Brian R. Hunt I. Szunyogh M. Girvan Edward Ott 186 42 0 15 Feb 2021
Fading memory echo state networks are universal Lukas Gonon Juan-Pablo Ortega 183 67 0 22 Oct 2020
Risk bounds for reservoir computing Lukas Gonon Lyudmila Grigoryeva Juan-Pablo Ortega 218 46 0 30 Oct 2019
Differentiable reservoir computing Lyudmila Grigoryeva Juan-Pablo Ortega 250 46 0 16 Feb 2019
Reservoir Computing Universality With Stochastic InputsIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2018 Lukas Gonon Juan-Pablo Ortega 200 123 0 07 Jul 2018
Echo state networks are universal Lyudmila Grigoryeva Juan-Pablo Ortega 275 259 0 03 Jun 2018
Universal discrete-time reservoir computers with stochastic inputs and linear readouts using non-homogeneous state-affine systems Lyudmila Grigoryeva Juan-Pablo Ortega 173 70 0 03 Dec 2017
Model selection for weakly dependent time series forecasting Pierre Alquier Olivier Wintenberger OOD AI4TS 629 86 0 17 Feb 2009