Paper Citation Record · LEDGER

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks

As of 11 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2607.06079.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2607.06079 v2

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T08:34:22.698306Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

35 of 35 outbound references displayed

verified exact1
verified fuzzy0
unresolved29
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malformed identifier5
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External citation measurements

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Outbound references

Observation c905570d-48f9-4490-befb-c0cbf5366544 · outbound

This paper cites Large-Scale Machine Learning with Stochastic Gradient Descent, in: Lechevallier, Y., Saporta, G.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Large-Scale Machine Learning with Stochastic Gradient Descent, in: Lechevallier, Y., Saporta, G

Reference 1

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Observation 1a99a266-4b5a-4135-9bbd-6c367b752aab · outbound

This paper cites (Eds.), 2013.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks (Eds.), 2013

Reference 2

Resolution: verified exact; doi, observed 2026-08-02T08:38:32.240349Z

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Observation b753a685-8247-4824-9778-6332405862c9 · outbound

This paper cites Méthode générale pour la résolution des systèmes d’équations simultanées.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Méthode générale pour la résolution des systèmes d’équations simultanées

Reference 3

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Observation 6e8a0536-5400-4452-a75e-a25efe1f9905 · outbound

This paper cites Infor- mation Processing Capacity of Dynamical Systems.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Infor- mation Processing Capacity of Dynamical Systems

Reference 4

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Observation d2539378-8727-4c23-b425-917582a6323e · outbound

This paper cites Gradient learning in spiking neural networks by dynamic perturbation of conductances.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Gradient learning in spiking neural networks by dynamic perturbation of conductances

Reference 5

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Observation 7863cead-c2e1-448b-bfcf-d50de1cbc5ad · outbound

This paper cites Summed Weight Neuron Pertur- bation: An O(N) Improvement Over Weight Perturbation, in: Advances in Neural Information Processing Systems, Morgan- Kaufmann.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Summed Weight Neuron Pertur- bation: An O(N) Improvement Over Weight Perturbation, in: Advances in Neural Information Processing Systems, Morgan- Kaufmann

Reference 6

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Observation 037c1dde-6ac0-47c7-b81b-858ee3e4c514 · outbound

This paper cites Theoria motus corporum coelestium in sectionibus coni- cis solem ambientium.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Theoria motus corporum coelestium in sectionibus coni- cis solem ambientium

Reference 7

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Observation 8bc6a4fd-811e-4600-8381-40fff47e87ef · outbound

This paper cites Learning Dynamics by Reservoir Computing (In Memory of Prof.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Learning Dynamics by Reservoir Computing (In Memory of Prof

Reference 8

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Observation e12a6d81-00af-464a-ac35-b5e8cd4ed3d5 · outbound

This paper cites Memory and Information Processing in Neuro- morphic Systems.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Memory and Information Processing in Neuro- morphic Systems

Reference 9

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Observation 8d6c0cba-9e38-4b40-bdad-c37474bfbc8d · outbound

This paper cites Weight Perturbation: An Optimal Archi- tecture and Learning Technique for Analog VLSI Feedforward and Re- current Multilayer Networks.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Weight Perturbation: An Optimal Archi- tecture and Learning Technique for Analog VLSI Feedforward and Re- current Multilayer Networks

Reference 10

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Observation 6ca96699-3b59-46e1-b5c2-097fbf7f63cc · outbound

This paper cites echo state.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks echo state

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T08:34:22.619573Z

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Observation e9db5878-ebfc-49fe-a006-8c7f861e3e53 · outbound

This paper cites Adaptive Nonlinear System Identification with Echo State Networks, in: Advances in Neural Information Processing Systems, MIT Press.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Adaptive Nonlinear System Identification with Echo State Networks, in: Advances in Neural Information Processing Systems, MIT Press

Reference 12

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Observation f98895ae-8cd5-48a8-a9d3-0600ba230e28 · outbound

This paper cites Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication

Reference 13

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Observation 5f35a45a-ab82-4d04-80fc-64bf4ba8da03 · outbound

This paper cites Nouvelles méthodes pour la détermination des or- bites des comètes.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Nouvelles méthodes pour la détermination des or- bites des comètes

Reference 15

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Observation 557ead07-f20f-41a7-bdb8-057233fffe01 · outbound

This paper cites Backpropagation and the brain.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Backpropagation and the brain

Reference 16

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Observation 2e10d192-49d0-44ef-94f7-7269061a7a95 · outbound

This paper cites On- DeviceTrainingUnder256KBMemory, in: AdvancesinNeuralInformation Processing Systems, Curran Associates, Inc.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks On- DeviceTrainingUnder256KBMemory, in: AdvancesinNeuralInformation Processing Systems, Curran Associates, Inc

Reference 17

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Observation fe9d5472-9d76-4149-8800-acbbe77c4f59 · outbound

This paper cites Reservoir observers: Model-free inference of unmeasured variables in chaotic systems.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Reservoir observers: Model-free inference of unmeasured variables in chaotic systems

Reference 18

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Observation adedac4d-e1e3-4183-a8c8-4f000eb04315 · outbound

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

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Reservoir computing approaches to recurrent neural network training

Reference 19

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Observation 01a2b473-eed7-4e68-8267-ca07cecca4a9 · outbound

This paper cites Real-Time Com- puting Without Stable States: A New Framework for Neural Compu- tation Based on Perturbations.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Real-Time Com- puting Without Stable States: A New Framework for Neural Compu- tation Based on Perturbations

Reference 20

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Observation 4d97a9f9-66ab-4d80-8008-1712d697fa9b · outbound

This paper cites Neuromorphic electronic systems.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Neuromorphic electronic systems

Reference 21

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Observation 1f65e654-34af-4196-b4fe-5b3f09c1cbe8 · outbound

This paper cites Con- tinual lifelong learning with neural networks: A review.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Con- tinual lifelong learning with neural networks: A review

Reference 22

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Observation d2f3ca1f-2a2f-4305-9a44-e01d615f7c91 · outbound

This paper cites Model-Free Predic- tion of Large Spatiotemporally Chaotic Systems from Data: A Reservoir Computing Approach.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Model-Free Predic- tion of Large Spatiotemporally Chaotic Systems from Data: A Reservoir Computing Approach

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-02T08:34:22.665288Z

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Observation 3a5dd396-3132-400d-8ec3-f0acd7ef7fb4 · outbound

This paper cites Some Theorems in Least Squares.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Some Theorems in Least Squares

Reference 24

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Observation e3044980-d462-46fe-bccf-912defee4a50 · outbound

This paper cites Scaling forward gradient with local losses, in: The Eleventh International Conference on Learning Representations.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Scaling forward gradient with local losses, in: The Eleventh International Conference on Learning Representations

Reference 25

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Observation 9f1f9ffa-a48d-445e-8cb5-f037ddfa034d · outbound

This paper cites A Stochastic Approximation Method.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks A Stochastic Approximation Method

Reference 26

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Observation 96dbd64d-9349-438c-a30c-2d153a1672c2 · outbound

This paper cites Generating coherent patterns of activity fromchaoticneuralnetworks.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Generating coherent patterns of activity fromchaoticneuralnetworks

Reference 27

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Observation f47962cc-084b-4518-8fa0-0e013aa1eea6 · outbound

This paper cites Recent advances in physical reservoir computing: A review.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Recent advances in physical reservoir computing: A review

Reference 28

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Observation a612885e-3b3a-42c0-ad57-542a8851e95e · outbound

This paper cites Learning curves for stochastic gradi- ent descent in linear feedforward networks.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Learning curves for stochastic gradi- ent descent in linear feedforward networks

Reference 29

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Observation b0a7145d-a621-4851-92e1-bcc5c5805d8c · outbound

This paper cites Numerical Evaluation of a Weakly Supervised Filtering Method Based on Echo State Networks.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Numerical Evaluation of a Weakly Supervised Filtering Method Based on Echo State Networks

Reference 30

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Observation 7df931d0-6016-4b81-9d06-13154a2b9935 · outbound

This paper cites UnsupervisedLearninginEcho StateNetworksforInputReconstruction.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks UnsupervisedLearninginEcho StateNetworksforInputReconstruction

Reference 31

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Observation 98522011-508c-441b-ac48-76a7e3858ea7 · outbound

This paper cites Weight versus Node Perturbation Learning in Temporally Extended Tasks: Weight Per- turbation Often Performs Similarly or Better.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Weight versus Node Perturbation Learning in Temporally Extended Tasks: Weight Per- turbation Often Performs Similarly or Better

Reference 32

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Observation 786a3246-df2e-4d15-89f7-16a3c686d634 · outbound

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Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Unresolved cited work

Reference 80

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Observation 82df3c9a-a968-43c1-8679-a833599db9a9 · outbound

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Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Unresolved cited work

Reference 123

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Observation 30f8da1b-f83e-4826-8f0e-e453f9129ed9 · outbound

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Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Unresolved cited work

Reference 149

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Observation 5db2acaf-a8ef-40cb-af01-0dc11c0c2994 · outbound

This paper cites an unresolved cited work.

Scalable Perturbation Learning for Online Self-Supervised Learning in Echo State Networks Unresolved cited work

Reference 2718

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Pith citing papers

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