Cover Image

Asymmetrically connected reservoir networks learn better

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Rathor, Shailendra K., Ziegler, Martin, Schumacher, Jörg
Format:	Preprint
Published:	2024
Subjects:	Neural and Evolutionary Computing Chaotic Dynamics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Prediction performance of random reservoirs with different topology for nonlinear dynamical systems with different number of degrees of freedom
by: Rathor, Shailendra K., et al.
Published: (2025)

Jump-diffusion models of parametric volume-price distributions
by: Budhathoki, Anup, et al.
Published: (2025)

Identification of fixations and saccades in eye-tracking data using adaptive threshold-based method
by: Orioma, Charles, et al.
Published: (2025)

Integer-State Dynamics of Quantized Spiking Neural Networks for Efficient Hardware Acceleration
by: Zhang, Lei
Published: (2026)

Learning Continuous Chaotic Attractors with a Reservoir Computer
by: Smith, Lindsay M., et al.
Published: (2021)

The boundary of neural network trainability is fractal
by: Sohl-Dickstein, Jascha
Published: (2024)

Reconstruction of dynamic systems using genetic algorithms with dynamic search limits
by: Rodríguez-Abreo, Omar, et al.
Published: (2024)

Reconfigurable Nonlinear Photonic Networks for In-Situ Learning and Memory Formation via Driven-Dissipative Dynamics
by: Yorke, Isaac
Published: (2026)

Chaotic Oscillator Networks for Classification Tasks
by: Ivas, Toni, et al.
Published: (2026)

Harnessing and modulating chaos to sample from neural generative models
by: Chaudhuri, Rishidev, et al.
Published: (2024)

Adjusting Dynamics of Hopfield Neural Network via Time-variant Stimulus
by: Peng, Xuenan, et al.
Published: (2024)

Analysis of chaotic dynamical systems with autoencoders
by: Almazova, N., et al.
Published: (2021)

Panda: A pretrained forecast model for chaotic dynamics
by: Lai, Jeffrey, et al.
Published: (2025)

Denoising and Reconstruction of Nonlinear Dynamics using Truncated Reservoir Computing
by: Sedehi, Omid, et al.
Published: (2025)

Reservoir computing with logistic map
by: Arun, R., et al.
Published: (2024)

Designing Chaotic Attractors: A Semi-supervised Approach
by: Kabayama, Tempei, et al.
Published: (2024)

Attractor-merging Crises and Intermittency in Reservoir Computing
by: Kabayama, Tempei, et al.
Published: (2025)

Reservoir Computing with a Single Oscillating Gas Bubble: Emphasizing the Chaotic Regime
by: Abdel-Ghani, Hend, et al.
Published: (2025)

Hierarchy of chaotic dynamics in random modular networks
by: Kuśmierz, Łukasz, et al.
Published: (2024)

Freezing chaos without synaptic plasticity
by: Huang, Weizhong, et al.
Published: (2025)

Machine Learning of Nonlinear Dynamical Systems with Control Parameters Using Feedforward Neural Networks
by: Sakaguchi, Hidetsugu
Published: (2024)

How high dimensional neural dynamics are confined in phase space
by: Wang, Shishe, et al.
Published: (2024)

Controlling Chaotic Maps using Next-Generation Reservoir Computing
by: Kent, Robert M., et al.
Published: (2023)

Proposed modified computational model for the amoeba-inspired combinatorial optimization machine
by: Miyajima, Yusuke, et al.
Published: (2024)

Physical Reservoir Computing Enabled by Solitary Waves and Biologically-Inspired Nonlinear Transformation of Input Data
by: Maksymov, Ivan S.
Published: (2024)

Enhancing Computational Efficiency in Multiscale Systems Using Deep Learning of Coordinates and Flow Maps
by: Hamid, Asif, et al.
Published: (2024)

Counting Short Trajectories in Elementary Cellular Automata using the Transfer Matrix Method
by: Koller, Cédric, et al.
Published: (2025)

Classical and Quantum Physical Reservoir Computing for Onboard Artificial Intelligence Systems: A Perspective
by: Abbas, A. H., et al.
Published: (2024)

Revisiting time-variant complex conjugate matrix equations with their corresponding real field time-variant large-scale linear equations, neural hypercomplex numbers space compressive approximation approach
by: He, Jiakuang, et al.
Published: (2024)

Topologically protected synchronization in networks
by: Ostilli, Massimo
Published: (2025)

Exploring the origins of switching dynamics in a multifunctional reservoir computer
by: Flynn, Andrew, et al.
Published: (2024)

Global stability of a Hebbian/anti-Hebbian network for principal subspace learning
by: Lipshutz, David, et al.
Published: (2026)

Emergent oscillations and chaos in non-compliant microfluidic networks
by: Shao, Yanxuan, et al.
Published: (2025)

Entropy Production Rate in Stochastically Time-evolving Asymmetric Networks
by: Pham, Tuan, et al.
Published: (2026)

Chimera states in neural networks and power systems
by: Deng, Shengfeng, et al.
Published: (2023)

A theoretical framework for reservoir computing on networks of organic electrochemical transistors
by: Landry, Nicholas W., et al.
Published: (2024)

Can multivariate Granger causality detect directed connectivity of a multistable and dynamic biological decision network model?
by: Asadpour, Abdoreza, et al.
Published: (2024)

Linear Simple Cycle Reservoirs at the edge of stability perform Fourier decomposition of the input driving signals
by: Fong, Robert Simon, et al.
Published: (2024)

Analysis of the Geometric Structure of Neural Networks and Neural ODEs via Morse Functions
by: Kuehn, Christian, et al.
Published: (2024)

AutoTurb: Using Large Language Models for Automatic Algebraic Model Discovery of Turbulence Closure
by: Zhang, Yu, et al.
Published: (2024)