mlsanityData to 7 Oct 2026

Deep Echo State Network (DeepESN): A Brief Survey

arXiv 1712.04323 ↗First posted 12 Dec 2017cs.LG cs.AI stat.MLcited by 21

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Abstract (arXiv)

The study of deep recurrent neural networks (RNNs) and, in particular, of deep Reservoir Computing (RC) is gaining an increasing research attention in the neural networks community. The recently introduced Deep Echo State Network (DeepESN) model opened the way to an extremely efficient approach for designing deep neural networks for temporal data. At the same time, the study of DeepESNs allowed to shed light on the intrinsic properties of state dynamics developed by hierarchical compositions of recurrent layers, i.e. on the bias of depth in RNNs architectural design. In this paper, we summarize the advancements in the development, analysis and applications of DeepESNs.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Dec 2017.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 4; 2022: 6; 2023: 1; 2024: 2; 2025: 5; 2026: 3.

21 papers.

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  1. 2021TE-ESN: Time Encoding Echo State Network for Prediction Based on Irregularly Sampled Time Series Datacited by 10
  2. 2021Elastic Similarity and Distance Measures for Multivariate Time Seriescited by 8
  3. 2023Spiking Neural Networks and Bio-Inspired Supervised Deep Learning: A Surveycited by 8
  4. 2021On the Post-hoc Explainability of Deep Echo State Networks for Time Series Forecasting, Image and Video Classificationcited by 3
  5. 2022Analysis, Characterization, Prediction and Attribution of Extreme Atmospheric Events with Machine Learning: a Reviewcited by 3
  6. 2025MH-GIN: Multi-scale Heterogeneous Graph-based Imputation Network for AIS Data (Extended Version)cited by 3
  7. 2022Evolutionary Echo State Network: evolving reservoirs in the Fourier spacecited by 2
  8. 2022LETS-GZSL: A Latent Embedding Model for Time Series Generalized Zero Shot Learningcited by 2
  9. 2022Re-visiting Reservoir Computing architectures optimized by Evolutionary Algorithmscited by 2
  10. 2025From Neurons to Computation: Biological Reservoir Computing for Pattern Recognitioncited by 2
  11. 2025Echo State Networks as State-Space Models: A Systems Perspectivecited by 2
  12. 2022Empirical Analysis of Limits for Memory Distance in Recurrent Neural Networkscited by 1
9 more
  1. 2024Recurrent Stochastic Configuration Networks with Incremental Blockscited by 1
  2. 2025From Neural Activity to Computation: Biological Reservoirs for Pattern Recognition in Digit Classificationcited by 1
  3. 2026Echo State Networks for Time Series Forecasting: Hyperparameter Sweep and Benchmarkingcited by 1
  4. 2026Neuro-Inspired Visual Pattern Recognition via Biological Reservoir Computingcited by 1
  5. 2026Rethinking Random Transformers as Adaptive Sequence Smoothers for Sleep Stagingcited by 1
  6. 2021KNN, An Underestimated Model for Regional Rainfall Forecastingcited by 0
  7. 2022Heterogeneous Reservoir Computing Models for Persian Speech Recognitioncited by 0
  8. 2024Deep Recurrent Stochastic Configuration Networks for Modelling Nonlinear Dynamic Systemscited by 0
  9. 2025HypER: Hyperbolic Echo State Networks for Capturing Stretch-and-Fold Dynamics in Chaotic Flowscited by 0