Backpropagation Algorithms and Reservoir Computing in Recurrent Neural Networks for the Forecasting of Complex Spatiotemporal Dynamics

9 October 2019

Brian R. Hunt

Papers citing "Backpropagation Algorithms and Reservoir Computing in Recurrent Neural Networks for the Forecasting of Complex Spatiotemporal Dynamics"

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Title
Context parroting: A simple but tough-to-beat baseline for foundation models in scientific machine learning Yuanzhao Zhang William Gilpin AI4TS 27 0 0 16 May 2025
On the emergence of numerical instabilities in Next Generation Reservoir Computing Edmilson Roque dos Santos Erik Bollt 34 0 0 01 May 2025
All Optical Echo State Network Reservoir Computing Ishwar S Kaushik Peter J. Ehlers Daniel Soh 38 0 0 11 Apr 2025
Incorporating Coupling Knowledge into Echo State Networks for Learning Spatiotemporally Chaotic Dynamics Kuei-Jan Chu Nozomi Akashi Akihiro Yamamoto 37 0 0 02 Apr 2025
Detecting Financial Fraud with Hybrid Deep Learning: A Mix-of-Experts Approach to Sequential and Anomalous Patterns Diego Vallarino 25 1 0 01 Apr 2025
Data-Driven Forecasting of High-Dimensional Transient and Stationary Processes via Space-Time Projection Oliver T. Schmidt AI4TS 36 1 0 31 Mar 2025
Thermalizer: Stable autoregressive neural emulation of spatiotemporal chaos Chris Pedersen L. Zanna Joan Bruna 55 2 0 24 Mar 2025
Reservoir Network with Structural Plasticity for Human Activity Recognition Abdullah M. Zyarah Alaa M. Abdul-Hadi Dhireesha Kudithipudi 31 3 0 01 Mar 2025
State-space models are accurate and efficient neural operators for dynamical systems Zheyuan Hu Nazanin Ahmadi Daryakenari Qianli Shen Kenji Kawaguchi George Karniadakis Mamba AI4CE 75 13 0 28 Jan 2025
On the relationship between Koopman operator approximations and neural ordinary differential equations for data-driven time-evolution predictions Jake Buzhardt C. Ricardo Constante-Amores Michael D. Graham 73 2 0 20 Nov 2024
A scalable generative model for dynamical system reconstruction from neuroimaging data Eric Volkmann Alena Brändle Daniel Durstewitz G. Koppe AI4CE 33 2 0 05 Nov 2024
Reconstructing dynamics from sparse observations with no training on target system Zheng-Meng Zhai Jun-Yin Huang Benjamin D. Stern Y. Lai 35 1 0 28 Oct 2024
Almost-Linear RNNs Yield Highly Interpretable Symbolic Codes in Dynamical Systems Reconstruction Manuel Brenner Christoph Jürgen Hemmer Zahra Monfared Daniel Durstewitz AI4CE 43 2 0 18 Oct 2024
Poisson-Dirac Neural Networks for Modeling Coupled Dynamical Systems across Domains Razmik Arman Khosrovian Takaharu Yaguchi Hiroaki Yoshimura Takashi Matsubara AI4CE 29 0 0 15 Oct 2024
Asymmetrically connected reservoir networks learn better Shailendra K. Rathor Martin Ziegler Jörg Schumacher 11 0 0 01 Oct 2024
Stability analysis of chaotic systems in latent spaces Elise Özalp Luca Magri 49 3 0 01 Oct 2024
Zero-shot forecasting of chaotic systems Yuanzhao Zhang William Gilpin AI4TS 42 6 0 24 Sep 2024
Hardware-Friendly Implementation of Physical Reservoir Computing with CMOS-based Time-domain Analog Spiking Neurons Nanako Kimura Ckristian Duran Zolboo Byambadorj Ryosho Nakane Tetsuya Iizuka 22 0 0 18 Sep 2024
On latent dynamics learning in nonlinear reduced order modeling N. Farenga S. Fresca Simone Brivio Andrea Manzoni AI4CE 41 1 0 27 Aug 2024
4D-Var using Hessian approximation and backpropagation applied to automatically-differentiable numerical and machine learning models Kylen Solvik Stephen G. Penny Stephan Hoyer 26 2 0 05 Aug 2024
Higher order quantum reservoir computing for non-intrusive reduced-order models Saloua Naama R. Maulik 21 0 0 31 Jul 2024
Machine Learning for Predicting Chaotic Systems Christof Schötz Alistair J R White Maximilian Gelbrecht Niklas Boers AI4CE 41 4 0 29 Jul 2024
Weak baselines and reporting biases lead to overoptimism in machine learning for fluid-related partial differential equations N. McGreivy Ammar Hakim AI4CE 39 43 0 09 Jul 2024
Temporal Convolution Derived Multi-Layered Reservoir Computing Johannes Viehweg Dominik Walther Prof. Dr. -Ing. Patrick Mäder AI4TS 27 1 0 09 Jul 2024
Exploiting Heterogeneity in Timescales for Sparse Recurrent Spiking Neural Networks for Energy-Efficient Edge Computing Biswadeep Chakraborty Saibal Mukhopadhyay 38 2 0 08 Jul 2024
On instabilities in neural network-based physics simulators Daniel Floryan AI4CE 46 2 0 18 Jun 2024
Oscillations enhance time-series prediction in reservoir computing with feedback Yuji Kawai Takashi Morita Jihoon Park Minoru Asada AI4TS 31 1 0 05 Jun 2024
Reservoir Computing Benchmarks: a tutorial review and critique Chester Wringe Martin A. Trefzer Susan Stepney 24 2 0 10 May 2024
Solving Partial Differential Equations with Equivariant Extreme Learning Machines Hans Harder Jean Rabault Ricardo Vinuesa Mikael Mortensen Sebastian Peitz 46 3 0 29 Apr 2024
Forecasting the Forced van der Pol Equation with Frequent Phase Shifts Using Reservoir Computing Sho Kuno Hiroshi Kori 18 0 0 23 Apr 2024
Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales for Pruning Recurrent SNN Biswadeep Chakraborty Beomseok Kang H. Kumar Saibal Mukhopadhyay 46 8 0 06 Mar 2024
Hybridizing Traditional and Next-Generation Reservoir Computing to Accurately and Efficiently Forecast Dynamical Systems Ravi Chepuri Dael Amzalag Thomas Antonsen M. Girvan 27 9 0 04 Mar 2024
Out-of-Domain Generalization in Dynamical Systems Reconstruction Niclas Alexander Göring Florian Hess Manuel Brenner Zahra Monfared Daniel Durstewitz AI4CE 43 12 0 28 Feb 2024
DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems Yair Schiff Zhong Yi Wan Jeffrey B. Parker Stephan Hoyer Volodymyr Kuleshov Fei Sha Leonardo Zepeda-Núñez 36 13 0 06 Feb 2024
RefreshNet: Learning Multiscale Dynamics through Hierarchical Refreshing Junaid Farooq Danish Rafiq Pantelis R. Vlachas M. A. Bazaz 34 0 0 24 Jan 2024
Small jet engine reservoir computing digital twin Colton J. Wright Nicholas Biederman Brian Gyovai Daniel J. Gauthier Jay P. Wilhelm 20 0 0 15 Dec 2023
An exact mathematical description of computation with transient spatiotemporal dynamics in a complex-valued neural network Roberto C. Budzinski Alexandra N. Busch Samuel Mestern Erwan Martin L. Liboni F. Pasini Ján Mináč Todd Coleman Wataru Inoue L. Muller 25 4 0 28 Nov 2023
Machine-learning parameter tracking with partial state observation Zheng-Meng Zhai Mohammadamin Moradi Bryan Glaz Mulugeta Haile Ying-Cheng Lai 32 7 0 15 Nov 2023
Bifurcations and loss jumps in RNN training Lukas Eisenmann Zahra Monfared Niclas Alexander Göring Daniel Durstewitz 24 9 0 26 Oct 2023
Tasks Makyth Models: Machine Learning Assisted Surrogates for Tipping Points Gianluca Fabiani N. Evangelou Tianqi Cui J. M. Bello-Rivas Cristina P. Martin-Linares Constantinos Siettos Ioannis G. Kevrekidis 40 2 0 25 Sep 2023
Control-aware echo state networks (Ca-ESN) for the suppression of extreme events A. Racca Luca Magri 11 2 0 06 Aug 2023
Variability of echo state network prediction horizon for partially observed dynamical systems Ajit Mahata Reetish Padhi A. Apte 26 1 0 19 Jun 2023
Generalized Teacher Forcing for Learning Chaotic Dynamics Florian Hess Zahra Monfared Manuela Brenner Daniel Durstewitz AI4CE 37 31 0 07 Jun 2023
Reconstruction, forecasting, and stability of chaotic dynamics from partial data Elise Özalp G. Margazoglou Luca Magri AI4TS 18 10 0 24 May 2023
Temporal Subsampling Diminishes Small Spatial Scales in Recurrent Neural Network Emulators of Geophysical Turbulence T. A. Smith S. Penny Jason A. Platt Tse-Chun Chen 27 5 0 28 Apr 2023
Constraining Chaos: Enforcing dynamical invariants in the training of recurrent neural networks Jason A. Platt S. Penny T. A. Smith Tse-Chun Chen H. Abarbanel AI4TS 38 5 0 24 Apr 2023
Adaptive learning of effective dynamics: Adaptive real-time, online modeling for complex systems Ivica Kicic Pantelis R. Vlachas G. Arampatzis Michail Chatzimanolakis Leonidas J. Guibas Petros Koumoutsakos AI4CE 24 6 0 04 Apr 2023
Model scale versus domain knowledge in statistical forecasting of chaotic systems W. Gilpin AI4TS 43 17 0 13 Mar 2023
Learning from Predictions: Fusing Training and Autoregressive Inference for Long-Term Spatiotemporal Forecasts Pantelis R. Vlachas Petros Koumoutsakos AI4TS AI4CE 23 7 0 22 Feb 2023
Physics-Informed Long Short-Term Memory for Forecasting and Reconstruction of Chaos Elise Özalp G. Margazoglou Luca Magri AI4TS 14 3 0 03 Feb 2023