Reservoir Computing

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Reservoir computing studies how the evolving states of recurrent systems can encode useful information about time-varying inputs, often without training the recurrent connections. Common approaches include echo state networks with fitted linear readouts, next-generation reservoirs built from delays and nonlinear features, and physical reservoirs based on devices such as photonic, memristive, mechanical, or biological systems. Researchers apply these methods to chaotic-system forecasting, signal classification, control, and scientific modeling, while improving them through changes to topology, timescales, pruning, and online adaptation. A central challenge is balancing memory, stability, and expressive dynamics; for quantum reservoirs in particular, broad advantages over carefully matched classical methods remain unestablished.

Latest papers

107 papers10 papers in the last four weeks, down 17% on the four weeks before. 0.1% of all new papers.

HiRo: A Compact Four-Directional Hierarchical Reservoir Token-Mixer for Efficient Image Classification
Jun 13, 2026Md Farhadul Islam, Ishan Thakkar, J. Todd HastingsReservoir Computing Image Classification
University of Kentucky · Lexington, USA
Quantum Reservoir Computing for Short-Term Power Load Forecasting in Resource-Constrained Energy Systems
Jun 11, 2026Mansi Od, Param Pathak, Nouhaila Innan +1Time Series Forecasting Reservoir Computing
University of Greenwich, London, United Kingdom · Fractal Analytics, QuantumAI Lab, Mumbai, Maharashtra, India · eBRAIN Lab, Division of Engineering, New York University Abu Dhabi (NYUAD), Abu Dhabi, UAE +1
PCA-Enhanced Adaptive NVAR Framework for High-Resolution Sea Surface Temperature Forecasting in the East Sea
Jun 10, 2026Sherkhon Azimov, Susana López-Moreno, Eric Dolores-Cuenca +2Neural Surrogate Modeling Reservoir Computing
Department of Mathematics, Pusan National University, Republic of Korea · Humanoid Olfactory Display Center, Pusan National University, Republic of Korea · Industrial Mathematics Center, Pusan National University, Republic of Korea +3
Effective Training Principles of Physical Reservoirs
Jun 8, 2026Sobhi Saeed, Mehmet Müftüoglu, Glitta R. Cheeran +3Reservoir Computing
LEIBNIZ-INSTITUTE OF PHOTONIC TECHNOLOGY,2026 ALBERT-EINSTEIN-STR. 9, 07745 JENA, GERMANY · INSTITUTE OF APPLIED OPTICS AND BIOPHYSICS, FRIEDRICH SCHILLER UNIVERSITY JENA, HELMHOLTZWEG 4, 07745 JENA,Jun GERMANY
Between Amnesia and Chaos: A Memory Stability Expressivity Trilemma for Trainable Dissipative Oscillator Networks
Jun 7, 2026Caleb MunigetyDynamical Systems Lyapunov Stability
Independent Researcher
The Whale That Outswam Evolution: Swarm Intelligence Maximises Memory in Connectome Reservoirs
Jun 5, 2026Anmol Guragain, Savvas Kakalis, Juan Ignacio Godino-LlorenteMetaheuristic Optimization Reservoir Computing
ETSI de Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain
Short-Term Synaptic Plasticity Stabilizes Goal-Conditioned Dynamics in a PFC-Inspired Reservoir Model for Multistep Goal-Directed Action Planning
Jun 2, 2026Jin Nakamura, Yuichi KatoriComputational Cognitive Modeling Reservoir Computing
Graduate School of Information Science and Technology, The University of Osaka, 1-5 Yamadaoka, Suita, 565-0871, Osaka, Japan · School of Systems Information Science, Future University Hakodate, 116-2 Kamedanakano-cho, Hakodate, 041-8655, Hokkaido, Japan
Flow map learning in nonlinear vector autoregressive models: influence of the feature-library structure on the training error
May 29, 2026Markus GrossKoopman Operator Learning Nonlinear System Identification
Institute for AI Safety and Security, German Aerospace Center (DLR), Sankt Augustin and Ulm, Germany
Deep Binarized Photonic Reservoir Computing for Ultrafast Multimedia Signal Processing
May 28, 2026Muhammad Waqar Iqbal, Mohamad Alassir, Nicolas Marsal +1Binary Neural Networks Reservoir Computing
Universit´e de Lorraine, CentraleSup´elec, LMOPS Laboratory, F-57070 Metz, France · Chaire Photonique, LMOPS Laboratory, CentraleSup´elec, F-57070 Metz, France
Adaptive Reservoir Computing for Multi-Scenario Chaotic System Forecasting
May 27, 2026Shadmehr Zaregarizi, Khashayar YavariDynamic Neural Networks Forecasting Benchmarks
Politecnico di Torino Turin, Italy
Data-Specific Hyper-Parameter Design: A Paradigm Shift in Reservoir Computing
May 24, 2026G Manjunath, Juan-Pablo Ortega, Alma van der MerweTime Series Forecasting Reservoir Computing
University of Pretoria. Department of Mathematics and Applied Mathematics. Pretoria 0002, South Africa. · Nanyang Technological University. Division of Mathematical Sciences. School of Physical and Mathematical Sciences. Singapore.
Memory Uncertainty Relation and Harmonic Memory in Random Recurrent Networks
May 23, 2026Taichi Haruna, Kohei NakajimaRecurrent Neural Networks Reservoir Computing
Department of Information and Mathematical Sciences, School of Arts and Sciences, Tokyo Woman’s Christian University, 2-6-1 Zempukuji, Suginami-ku, Tokyo 167-8585, Japan · Graduate School of Information Science and Technology, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656, Japan
Evolutionary Algorithm for Reservoir Learning and Yielding
May 19, 2026Julien Testu, Pierrick Legrand, Xavier HinautReservoir Computing Neural Architecture Search
UB, Mnemosyne · ENSC, Bordeaux INP · Mnemosyne
Controllable Quantum Memory Capacity in Quantum Reservoir Networks with Tunable partial-SWAPs
May 12, 2026Erik L. Connerty, Ethan N. EvansReservoir Computing Quantum Reservoir Computing
University of South Carolina - Columbia, Columbia, SC, USA · Qodex Quantum, Chicago, IL, USA
A Random-Matrix Criterion for Initializing Gated Recurrent Neural Networks
May 11, 2026Tommaso Fioratti, Riccardo Marcaccioli, Francesco CasolaGated Recurrent Unit Neural Network Initialization
Capital Fund Management, 75007 Paris, France · Institute of Mathematics, EPFL, 1015 Lausanne, Switzerland
Medical Imaging Classification with Cold-Atom Reservoir Computing using Auto-Encoders and Surrogate-Driven Training
May 7, 2026Nuno Batista, Ana Morgado, Oscar Ferraz +3Medical Image Analysis Hybrid Quantum-Classical ML
Instituto de Telecomunicações, Dept. of Electrical and Computer Engineering, University of Coimbra, Portugal · CFisUC, Department of Physics, University of Coimbra, Portugal · ISR - Institute of Systems and Robotics, Dept. of Electrical and Computer Engineering, University of Coimbra, Portugal
Koopman Identification of Nonlinear Systems via Reservoir Liftings
May 6, 2026Weibin Gu, Chen Yang, Lu ShiKoopman Operator Learning Nonlinear System Identification
Institute for AI Industry Research (AIR), Tsinghua University, Beijing, PR China · School of Engineering, China University of Petroleum-Beijing at Karamay, Xinjiang Uygur Autonomous Region, PR China
Inferring bifurcation diagrams of two distinct chaotic systems by a single machine
Apr 29, 2026Jianmin Guo, Yao Du, Yizhen Yu +2Dynamical Systems Nonlinear System Identification
School of Physics and Information Technology, Shaanxi Normal University, Xi’an 710062, China · College of Physics and Electronic Information Engineering, Qinghai Normal University, Xining 810008, China · School of Physics and Electronic Science, East China Normal University, Shanghai 200062, China
Neuromorphic Computing Based on Parametrically-Driven Oscillators and Frequency Combs
Apr 23, 2026Mahadev Sunil Kumar, Adarsh GanesanDynamical Systems Reservoir Computing
Amrita School of Computing, Amrita Vishwa Vidyapeetham, Kollam, India 690525 · Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science, Pilani – Dubai Campus, Dubai, United Arab Emirates 345055
On the Role of Preprocessing and Memristor Dynamics in Reservoir Computing for Image Classification
Apr 23, 2026Rishona Daniels, Duna Wattad, Ronny Ronen +2Reservoir Computing Neuromorphic Computing
Viterbi Faculty of Electrical and Computing Engineering, Technion - Israel Institute of Technology, Haifa, Israel · College of Engineering and Physical Sciences, Aston University, Birmingham B4 7ET, United Kingdom
Scalable Memristive-Friendly Reservoir Computing for Time Series Classification
Apr 21, 2026Coşku Can Horuz, Andrea Ceni, Claudio Gallicchio +1Dynamic Neural Networks Energy-Efficient ML
Adaptive AI Research Group University of Lübeck, Germany · Department of Computer Science University of Pisa, Italy
What Makes a Bacterial Model a Good Reservoir Computer? Predicting Performance from Separability and Similarity
Apr 17, 2026Laura Alonso Bartolomé, Jean-Loup Faulon, Xavier HinautReservoir Computing
MICALIS, Mnemosyne · University Paris Saclay, INRAE, AgroParisTech, MICALIS Institute, 78350 Jouy-en-Josas, France · Centre Inria de l’Universit´e de Bordeaux, France +4
Vestibular reservoir computing
Apr 10, 2026Smita Deb, Shirin Panahi, Mulugeta Haile +1Reservoir Computing
School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, AZ 85287, USA · Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, CO 80523, USA · DEVCOM Army Research Office, 6340 Rodman Road, Aberdeen Proving Ground, MD 21005-5069, USA +1
OpenPRC: A Unified Open-Source Framework for Physics-to-Task Evaluation in Physical Reservoir Computing
Apr 8, 2026Yogesh Phalak, Wen Sin Lor, Apoorva Khairnar +3Reservoir Computing Physics-Based Simulation
Department of Mechanical Engineering, Virginia Tech, Blacksburg, VA, USA · Department of Philosophy, Virginia Tech, Blacksburg, VA, USA · Department of Computer Science, Virginia Tech, Blacksburg, VA, USA
CBM-Dual: A 65-nm Fully Connected Chaotic Boltzmann Machine Processor for Dual Function Simulated Annealing and Reservoir Computing
Apr 8, 2026Kanta Yoshioka, Soshi Hirayae, Yuichiro Tanaka +3Energy-Efficient ML Reservoir Computing
Kyushu Institute of Technology, Kitakyushu, Japan · Future University Hakodate, Hakodate, Japan
Anticipating tipping in spatiotemporal systems with machine learning
Apr 7, 2026Smita Deb, Zheng-Meng Zhai, Mulugeta Haile +1Spatiotemporal Forecasting Reservoir Computing
School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, AZ 85287, USA · DEVCOM Army Research Office, 6340 Rodman Road, Aberdeen Proving Ground, MD 21005-5069, USA · Department of Physics, Arizona State University, Tempe, Arizona 85287, USA
Bridging Theory and Practice in Crafting Robust Spiking Reservoirs
Apr 7, 2026Ruggero Freddi, Nicolas Seseri, Diana Nigrisoli +1Reservoir Computing Spiking Neural Networks
Research and Development Department, Manava.plus, Milan, Italy · Department of Engineering and Geology, “G’. d’Annunzio” University of Chieti-Pescara, Pescara, Italy
On Dominant Manifolds in Reservoir Computing Networks
Apr 7, 2026Noa Kaplan, Alberto Padoan, Anastasia BizyaevaTime Series Forecasting Reservoir Computing
Department of Computer Science at Cornell University, Ithaca, NY, USA 14853 · Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC V6T 1Z4, Canada · Sibley School of Mechanical and Aerospace Engineering at Cornell University, Ithaca, NY, USA, 14853
Computing with Living Neurons: Chaos-Controlled Reservoir Computing with Knowledge Transplant
Apr 2, 2026Seung Hyun Kim, Zhi Dou, Gaurav Upadhyay +6Reservoir Computing Neuromorphic Computing
Mechanical Science and Engineering, University of Illinois Urbana-Champaign · Electrical and Computer Engineering, University of Illinois Urbana-Champaign · Coordinated Science Laboratory, University of Illinois Urbana-Champaign +6
Reservoir observer enhanced with residual calibration and attention mechanism
Apr 1, 2026Yichen Liu, Wei Xiao, Tianguang ChuReservoir Computing State Space Models
School of Advanced Manufacturing and Robotics, Peking University, Beijing 100871, China

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HiRo: A Compact Four-Directional Hierarchical Reservoir Token-Mixer for Efficient Image Classification

Md Farhadul Islam, Ishan Thakkar, J. Todd Hastings

University of Kentucky · Lexington, USA

Reservoir Computing Image Classification

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Recent image classification models must balance local feature modeling, cross-window interaction, and parameter efficiency. Many high-performing architectures rely on fully trainable token-mixers, which improve representation learning but increase parameter count, optimization complexity and computational cost. We propose a parameter-efficient image classification model called HiRo that integrates shifted-window partitioning with multi-directional hierarchical reservoir computing. Images are divided into non-overlapping patches (treated as tokens), linearly projected, normalized, and enriched with 2D sinusoidal positional encodings, then processed within local windows. Inside each window, tokens are scanned in four directions and passed through a two-stage slice-and-mix reservoir module. In the first stage, directional sequences are split into contiguous slices, each processed by its own fixed reservoir with a trainable closed-loop readout. The resulting slice outputs are summarized using the start, end, and mean representations, and then mixed by a second-stage fixed reservoir for each direction. The mixed slice representations are expanded back to the token level and fused with the first-stage outputs, after which the four directional outputs are realigned and averaged. Consecutive blocks alternate between regular and shifted windows to enable cross-window interaction, followed by layer normalization, a residual feed-forward network, and global pooling for classification. This design combines regular and shifted window partitioning with hierarchical multi-directional reservoirs to make an efficient local-to-cross-window token-mixing framework for image classification. Despite using under 1M trainable parameters and significantly lower memory and time than transformer-style baselines, HiRo also achieves 99.46%, 85.57%, and 59.10% accuracy on MNIST, CIFAR-10, and CIFAR-100, respectively.