Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks | Paper Citation Record

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This paper cites Climate data online.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Climate data online

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Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Residential electricity consumption data

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This paper cites Investigating Echo State Networks dynamics by means of recurrence analysis.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Investigating Echo State Networks dynamics by means of recurrence analysis

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This paper cites What is the state of neural network pruning? Proceedings of Machine Learning and Systems, 2: 0 129--146, 2020.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks What is the state of neural network pruning? Proceedings of Machine Learning and Systems, 2: 0 129--146, 2020

Reference 4

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This paper cites Centrality measures in networks.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Centrality measures in networks

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This paper cites On the sensitivity of centrality metrics.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks On the sensitivity of centrality metrics

Reference 6

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This paper cites Recurrent neural network pruning using dynamical systems and iterative fine-tuning.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Recurrent neural network pruning using dynamical systems and iterative fine-tuning

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This paper cites Pruning and regularization in reservoir computing.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Pruning and regularization in reservoir computing

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This paper cites Data-efficient structured pruning via submodular optimization.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Data-efficient structured pruning via submodular optimization

Reference 9

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This paper cites The lottery ticket hypothesis: Finding sparse, trainable neural networks.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks The lottery ticket hypothesis: Finding sparse, trainable neural networks

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This paper cites SPDY : Accurate pruning with speedup guarantees.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks SPDY : Accurate pruning with speedup guarantees

Reference 11

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This paper cites Centrality in social networks: Conceptual clarification.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Centrality in social networks: Conceptual clarification

Reference 12

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This paper cites Local Lyapunov exponents of deep Echo State Networks.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Local Lyapunov exponents of deep Echo State Networks

Reference 14

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Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Unresolved cited work

Reference 17

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This paper cites Sparse double descent: Where network pruning aggravates overfitting.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Sparse double descent: Where network pruning aggravates overfitting

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This paper cites Semi-supervised Echo State Network with partial correlation pruning for time-series variables prediction in industrial processes.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Semi-supervised Echo State Network with partial correlation pruning for time-series variables prediction in industrial processes

Reference 19

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This paper cites The ``Echo State'' approach to analysing and training recurrent neural networks---with an erratum note.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks The ``Echo State'' approach to analysing and training recurrent neural networks---with an erratum note

Reference 20

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This paper cites Optimization and applications of Echo State Networks with leaky-integrator neurons.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Optimization and applications of Echo State Networks with leaky-integrator neurons

Reference 21

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This paper cites No free prune: Information-theoretic barriers to pruning at initialization.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks No free prune: Information-theoretic barriers to pruning at initialization

Reference 22

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This paper cites ZipLM : Inference-aware structured pruning of language models.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks ZipLM : Inference-aware structured pruning of language models

Reference 23

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This paper cites Efficient behavior of small-world networks.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Efficient behavior of small-world networks

Reference 24

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This paper cites Broad Echo State Network with reservoir pruning for nonstationary time series prediction.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Broad Echo State Network with reservoir pruning for nonstationary time series prediction

Reference 26

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This paper cites Reservoir computing approaches to recurrent neural network training.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Reservoir computing approaches to recurrent neural network training

Reference 27

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This paper cites Convolutional multitimescale Echo State Network.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Convolutional multitimescale Echo State Network

Reference 28

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Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Oscillation and chaos in physiological control systems

Reference 29

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This paper cites Echo State Property linked to an input: Exploring a fundamental characteristic of recurrent neural networks.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Echo State Property linked to an input: Exploring a fundamental characteristic of recurrent neural networks

Reference 30

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This paper cites NREL wind integration national dataset toolkit.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks NREL wind integration national dataset toolkit

Reference 32

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Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks National solar radiation database ( NSRDB )

Reference 33

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This paper cites A high-performance deep reservoir computer experimentally demonstrated with ion-gating reservoirs.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks A high-performance deep reservoir computer experimentally demonstrated with ion-gating reservoirs

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This paper cites Fantastic weights and how to find them: Where to prune in dynamic sparse training.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Fantastic weights and how to find them: Where to prune in dynamic sparse training

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This paper cites Minimum complexity Echo State Network.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Minimum complexity Echo State Network

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This paper cites An effective criterion for pruning reservoir's connections in Echo State Networks.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks An effective criterion for pruning reservoir's connections in Echo State Networks

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Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Echo State Network optimization: A systematic literature review

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Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Deep Echo State Network pruning algorithm based on detrended multiple cross-correlation

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Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks An experimental unification of reservoir computing methods

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This paper cites Chain-structure Echo State Network with stochastic optimization: Methodology and application.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Chain-structure Echo State Network with stochastic optimization: Methodology and application

Reference 42

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Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Topology-aware network pruning using multi-stage graph embedding and reinforcement learning

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Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks One-Shot Pruning of Recurrent Neural Networks by Jacobian Spectrum Evaluation

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Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Information dynamics in neuromorphic nanowire networks

Reference 46

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This paper cites Scholarpedia , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Scholarpedia , volume =

Reference 47

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Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Reservoir Computing Approaches to Recurrent Neural Network Training , journal =

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Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Neural Networks , volume =

Reference 50

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Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks 2019 , publisher =

Reference 51

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This paper cites Real-Time Computing without Stable States: A New Framework for Neural Computation Based on Perturbations , journal =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Real-Time Computing without Stable States: A New Framework for Neural Computation Based on Perturbations , journal =

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Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Optimization and Applications of

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Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Training

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This paper cites 2014 International Joint Conference on Neural Networks (.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks 2014 International Joint Conference on Neural Networks (

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Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks 2012 , institution =

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This paper cites Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

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Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Frontiers in Computational Neuroscience , volume =

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Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Neural Networks , volume =

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Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Neural Computation , volume =

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Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks 2010 , publisher =

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Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Unresolved cited work

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This paper cites Engineering Applications of Artificial Intelligence , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Engineering Applications of Artificial Intelligence , volume =

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Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Proceedings of the

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This paper cites Journal of Intelligent & Fuzzy Systems , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Journal of Intelligent & Fuzzy Systems , volume =

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This paper cites Proceedings of the VLDB Endowment , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Proceedings of the VLDB Endowment , volume =

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This paper cites Computational Intelligence and Neuroscience , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Computational Intelligence and Neuroscience , volume =

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Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks 2023 , publisher =

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e64845cd-8049-491d-8b6a-5ef351efbaa0 · outbound

This paper cites Journal of Machine Learning Research , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Journal of Machine Learning Research , volume =

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:39.785604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2ca8f4ae-3ef9-48ee-a5eb-ed785d2c2980 · outbound

This paper cites Cognitive Computation , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Cognitive Computation , volume =

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:39.448099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f1434c4e-eec3-4287-8d39-567b42b8bf65 · outbound

This paper cites Measurement Science and Technology , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Measurement Science and Technology , volume =

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:39.073744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6e455408-8c95-4c1c-8ddf-0aa2c1024ec7 · outbound

This paper cites Social Choice and Welfare , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Social Choice and Welfare , volume =

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:38.790028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8d5dc8d9-b59e-4043-9b9e-a1fbff94a369 · outbound

This paper cites PLOS ONE , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks PLOS ONE , volume =

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:38.579801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4f24d997-0cee-43a0-8c4f-25d04d3053be · outbound

This paper cites Neural Processing Letters , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Neural Processing Letters , volume =

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:38.339919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5da34cea-d6ef-4f7c-9e26-ec719416a501 · outbound

This paper cites Social Networks , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Social Networks , volume =

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:38.246730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9cf8274c-5b7b-4248-84e0-37b1ef4f5c90 · outbound

This paper cites Scientific Reports , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Scientific Reports , volume =

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:38.187227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bf98354c-2cb8-4aae-8d00-f521c337b4ab · outbound

This paper cites PLOS ONE , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks PLOS ONE , volume =

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:37.977953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 31a08135-8753-4470-8180-9743f4e070d7 · outbound

This paper cites 2018 , publisher =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks 2018 , publisher =

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:37.847457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 80e85494-9019-468f-a0e6-e791b3dd4ff6 · outbound

This paper cites Science , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Science , volume =

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:37.736894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 43730b77-1e8a-4e8c-b4a7-40ee72e85746 · outbound

This paper cites Advances in Chemical Physics , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Advances in Chemical Physics , volume =

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:37.631167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0f7fe252-992c-4b8a-b638-df015885e006 · outbound

This paper cites an unresolved cited work.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Unresolved cited work

Reference 81

Resolution: unresolved; raw_fallback, observed 2026-08-06T21:19:37.513578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ce49f5ec-0092-4d6a-b5e2-81575c949d20 · outbound

This paper cites Proceedings of the 2019 11th International Conference on Machine Learning and Computing , year =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Proceedings of the 2019 11th International Conference on Machine Learning and Computing , year =

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:37.397908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 25e7ead9-e912-4a6e-bdd4-b832d3d136ba · outbound

This paper cites Feature-Based Echo-State Networks: A Step Towards Interpretability and Minimalism in Reservoir Computer.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Feature-Based Echo-State Networks: A Step Towards Interpretability and Minimalism in Reservoir Computer

Reference 83

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T21:19:29.167693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9aceb768-4a42-472d-b318-bcc87ccdf2f3 · outbound

This paper cites Proceedings of the 33rd International Conference on Machine Learning , pages =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Proceedings of the 33rd International Conference on Machine Learning , pages =

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:37.284202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a8fe313d-a97e-49bc-adb1-995e225b8304 · outbound

This paper cites Social Networks , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Social Networks , volume =

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:37.182477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0b863ea8-7318-4ea7-91a1-47132ec0ad63 · outbound

This paper cites The Science of Networks , journal =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks The Science of Networks , journal =

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:37.045969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 871a883e-eff2-4840-a461-4b07635a03c4 · outbound

This paper cites Physical Review Letters , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Physical Review Letters , volume =

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:36.945566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 71fff447-dd1f-47e1-a0f6-cd9651b09022 · outbound

This paper cites Social Networks , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Social Networks , volume =

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:36.818270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5396093c-07b3-46dc-be4d-92f8d825bcee · outbound

This paper cites Journal of Mathematical Sociology , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Journal of Mathematical Sociology , volume =

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:36.720882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2cc86a7c-9b51-4b74-a508-85e646f28271 · outbound

This paper cites Psychometrika , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Psychometrika , volume =

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:36.608705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 04f791d1-34ee-45e1-8644-fab1410c7bea · outbound

This paper cites Physica A: Statistical Mechanics and its Applications , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Physica A: Statistical Mechanics and its Applications , volume =

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:36.451099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5f6a2496-1edd-425f-ae6f-af97ac9d0826 · outbound

This paper cites and Rout, A.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks and Rout, A

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:36.307773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation dbfba554-95f7-495d-8f42-706cf725a4c0 · outbound

This paper cites and Stoffer, David S.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks and Stoffer, David S

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:36.169204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e503dc8b-1334-4ed2-9739-0cb07e732e82 · outbound

This paper cites and Nobre, C.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks and Nobre, C

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:35.992282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5e6d0f92-8f77-4b62-81a2-4250c233a523 · outbound

This paper cites , title =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks , title =

Reference 95

Resolution: parse uncertain; raw_fallback, observed 2026-08-06T21:19:35.845959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 17e0c5e7-0f3b-4c26-93b7-3cdc121dd5e3 · outbound

This paper cites Reservoir Computing Approaches to Recurrent Neural Network Training , journal =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Reservoir Computing Approaches to Recurrent Neural Network Training , journal =

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:35.695517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ac032a4f-e445-4259-8c3c-d542d8cebe6e · outbound

This paper cites and Zhang, H.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks and Zhang, H

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:35.556729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7d4b8bac-4143-4faf-945e-1cd5da01be4f · outbound

This paper cites and Min, X.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks and Min, X

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:35.419481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b8ea2780-ba93-4f36-b5ef-ab7178c278c3 · outbound

This paper cites an unresolved cited work.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Unresolved cited work

Reference 99

Resolution: unresolved; raw_fallback, observed 2026-08-06T21:19:35.260187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 678c21d0-de05-4bda-b067-0d549faa9b2d · outbound

This paper cites an unresolved cited work.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Unresolved cited work

Reference 100

Resolution: unresolved; raw_fallback, observed 2026-08-06T21:19:35.110072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 84b2a0f1-2adc-4dae-bfa3-960d69d7dfc7 · outbound

This paper cites Nachrichten von der Gesellschaft der Wissenschaften zu G.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Nachrichten von der Gesellschaft der Wissenschaften zu G

Reference 101

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:34.937184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b4d9e884-04c9-4bfa-9d55-fa8ba4b84a37 · outbound

This paper cites an unresolved cited work.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Unresolved cited work

Reference 102

Resolution: unresolved; raw_fallback, observed 2026-08-06T21:19:34.772456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 66550dce-150a-4665-b750-151e980c6347 · outbound

This paper cites , title =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks , title =

Reference 103

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:34.628913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 110f717f-6664-4af3-a39b-d0f2df7c7827 · outbound

This paper cites Psychometrika , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Psychometrika , volume =

Reference 104

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:34.422492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e77d7d5b-d033-4ee3-8e16-bcb4cc5b6fec · outbound

This paper cites American Journal of Sociology , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks American Journal of Sociology , volume =

Reference 105

Resolution: unresolved; no resolver link, observed 2026-08-06T21:19:23.030234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35dd6edb-369a-4a48-92ab-4aad23eb4cbf · outbound

This paper cites an unresolved cited work.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Unresolved cited work

Reference 106

Resolution: unresolved; raw_fallback, observed 2026-08-06T21:19:34.243547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1f42f41f-8e57-4689-8e91-818dba4bb97d · outbound

This paper cites Neurocomputing , volume =.

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks Neurocomputing , volume =

Reference 107

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:34.077243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers