ArticleNature communications2021
Next generation reservoir computing.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
82 citing papers in PubMed.
- Ferroelectric Transistors: from Materials Innovation to Intelligent Electronic Systems.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- Time series learning in a many-body Rydberg system with emergent collective amplification.Nature communications · 2026Article
- Coexisting Volatile and Nonvolatile Switching in 3D ALD-IGZO Vertical RRAM for Fully Hardware-Based Wide Reservoir Computing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- All-Optically Controlled Memristive Reservoir Computing Capable of Bipolar and Parallel Coding.Nature communications · 2026Article
- Tailored forecasting from short time series via meta-learning.Science advances · 2026Article
- Anisotropic Memristive Switching in NbOClAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Self-supervised reservoir computing with spatial-temporal encoding for identifying critical transitions.Nature communications · 2026Article
- Illuminating the black box of reservoir computing.Scientific reports · 2026Article
- Bacterial gene regulatory neural network as a biocomputing library of mathematical solvers.NPJ systems biology and applications · 2026Article
- Linearizing and Forecasting: A Reservoir Computing Route to Digital Twins of the Brain.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Adaptive state-feedback echo state networks for temporal sequence learning.Scientific reports · 2026Article
- Efficient next-generation reservoir computing: An analog in-memory implementation using memristor crossbar arrays.iScience · 2026Article
- Article
- A cascaded interferometer-microresonator structure for photonic reservoir computing.Scientific reports · 2026Article
- Ferroelectric nanodot reservoir for neuromorphic computing.Beilstein journal of nanotechnology · 2026Article
- Experimental memory control in continuous-variable optical quantum reservoir computing.Nature photonics · 2026Article
- Spatiotemporal Reservoir Computing with a Reconfigurable Multifunctional Memristor Array.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- Machine Learning-Based Prediction Framework for Complex Neuromorphic Dynamics of Third-Order Memristive Neurons at the Edge of Chaos.Entropy (Basel, Switzerland) · 2025Article
- Learning to learn ecosystems from limited data.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Tree-based learning for high-fidelity prediction of chaos.Scientific reports · 2025Article
22 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Reservoir computing is a best-in-class machine learning algorithm for processing information generated by dynamical systems using observed time-series data. Importantly, it requires very small training data sets, uses linear optimization, and thus requires minimal computing resources. However, the algorithm uses randomly sampled matrices to define the underlying recurrent neural network and has a multitude of metaparameters that must be optimized. Recent results demonstrate the equivalence of reservoir computing to nonlinear vector autoregression, which requires no random matrices, fewer metaparameters, and provides interpretable results. Here, we demonstrate that nonlinear vector autoregression excels at reservoir computing benchmark tasks and requires even shorter training data sets and training time, heralding the next generation of reservoir computing.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.