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Paper Citation Record · LEDGER

Recurrent Stochastic Configuration Networks with Incremental Blocks

As of 13 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 1 inbound Pith citation observation for arXiv:2411.11303.

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

pith.paper-citation-record.v1
2411.11303 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:50:29.948772Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:42:36.476148Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-12T12:42:36.507199Z

Reference resolution

30 of 30 outbound references displayed

  • verified exact0
  • verified fuzzy23
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ff0adc63-f157-42bf-b33c-b0122523fb9b · outbound

This paper cites A compre- hensive review for industrial applicability of artificial neural networks,.

Recurrent Stochastic Configuration Networks with Incremental Blocks A compre- hensive review for industrial applicability of artificial neural networks,

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation a746f5bf-7050-4215-a5b2-624edc39dfbc · outbound

This paper cites A deep dual adversarial network for cross-domain recommendation,.

Recurrent Stochastic Configuration Networks with Incremental Blocks A deep dual adversarial network for cross-domain recommendation,

Reference 2

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raw_fallback, observed 2026-08-12T18:50:30.153559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 49b7f8cd-d53c-44bf-81e2-314f1ae54d30 · outbound

This paper cites Multi-scale dynamic convolu- tional network for knowledge graph embedding,.

Recurrent Stochastic Configuration Networks with Incremental Blocks Multi-scale dynamic convolu- tional network for knowledge graph embedding,

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation ded5ae6d-6ec9-49c1-8c0d-5d693f2004ec · outbound

This paper cites On the difficulty of training recurrent neural networks, in International conference on machine learn- ing,.

Recurrent Stochastic Configuration Networks with Incremental Blocks On the difficulty of training recurrent neural networks, in International conference on machine learn- ing,

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation c0cc52ae-4c52-4110-8c11-570dba7133c7 · outbound

This paper cites Deep reservoir computing: A critical experimental analysis,.

Recurrent Stochastic Configuration Networks with Incremental Blocks Deep reservoir computing: A critical experimental analysis,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 048334c2-4a9e-49b8-826d-d2990e90e969 · outbound

This paper cites Periodic weather-aware LSTM with event mechanism for parking behavior pre- diction,.

Recurrent Stochastic Configuration Networks with Incremental Blocks Periodic weather-aware LSTM with event mechanism for parking behavior pre- diction,

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 0ed1bba4-94bf-492a-89e4-866099c69dae · outbound

This paper cites Survey: reservoir computing ap- proaches to recurrent neural network training,.

Recurrent Stochastic Configuration Networks with Incremental Blocks Survey: reservoir computing ap- proaches to recurrent neural network training,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation fa6874a5-6a77-4374-b277-6e19c8b48ca1 · outbound

This paper cites Randomness in neural networks: an overview,.

Recurrent Stochastic Configuration Networks with Incremental Blocks Randomness in neural networks: an overview,

Reference 8

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no resolver link, observed 2026-08-12T18:50:29.894067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 64c42134-3def-436a-ae6a-b0e558d07d0e · outbound

This paper cites The echo state approach to analysing and training recurrent neural networks-with an erratum note,.

Recurrent Stochastic Configuration Networks with Incremental Blocks The echo state approach to analysing and training recurrent neural networks-with an erratum note,

Reference 9

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no resolver link, observed 2026-08-12T18:50:29.896428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 263a35aa-5f34-4bcc-ab44-d18df4e28abe · outbound

This paper cites Real-time computing without stable states: a new framework for neural computation based on perturbations,.

Recurrent Stochastic Configuration Networks with Incremental Blocks Real-time computing without stable states: a new framework for neural computation based on perturbations,

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 1f2ebad1-34fb-47b1-97b2-b238d9c9873b · outbound

This paper cites Evolving dual-threshold bienenstock-cooper-munro learning rules in echo state networks,.

Recurrent Stochastic Configuration Networks with Incremental Blocks Evolving dual-threshold bienenstock-cooper-munro learning rules in echo state networks,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 2b6c22b2-197f-4f51-90d2-69ebe02e3a8c · outbound

This paper cites A systematic review of echo state networks from design to application,.

Recurrent Stochastic Configuration Networks with Incremental Blocks A systematic review of echo state networks from design to application,

Reference 12

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raw_fallback, observed 2026-08-12T18:50:30.089570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 898120d6-4f96-4396-9e84-578ce24ab498 · outbound

This paper cites Deep fuzzy echo state networks for machinery fault diagnosis,.

Recurrent Stochastic Configuration Networks with Incremental Blocks Deep fuzzy echo state networks for machinery fault diagnosis,

Reference 13

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raw_fallback, observed 2026-08-12T18:50:30.082500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 7cba8d65-7197-4413-9d01-30e98420dcba · outbound

This paper cites Minimum complexity echo state network,.

Recurrent Stochastic Configuration Networks with Incremental Blocks Minimum complexity echo state network,

Reference 14

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raw_fallback, observed 2026-08-12T18:50:30.075420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 6f231339-9f9d-453d-a909-7a4eb0b0b7c0 · outbound

This paper cites Optimization and applications of echo state networks with leaky-integrator neurons,.

Recurrent Stochastic Configuration Networks with Incremental Blocks Optimization and applications of echo state networks with leaky-integrator neurons,

Reference 15

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raw_fallback, observed 2026-08-12T18:50:30.067973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 7ace1a7a-c998-4106-a5e4-843517cd2b21 · outbound

This paper cites Echo state property of deep reservoir computing networks,.

Recurrent Stochastic Configuration Networks with Incremental Blocks Echo state property of deep reservoir computing networks,

Reference 16

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raw_fallback, observed 2026-08-12T18:50:30.060793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 6046dc2d-eca9-4c68-84f0-2d6125332f74 · outbound

This paper cites Deep Echo State Network (DeepESN): A Brief Survey.

Recurrent Stochastic Configuration Networks with Incremental Blocks Deep Echo State Network (DeepESN): A Brief Survey

Reference 17

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no resolver link, observed 2026-08-12T18:50:29.916253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 1351dc65-db31-4f5c-a0e1-376ab77d1ea2 · outbound

This paper cites Pruning and regular- ization in reservoir computing,.

Recurrent Stochastic Configuration Networks with Incremental Blocks Pruning and regular- ization in reservoir computing,

Reference 18

Resolution
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raw_fallback, observed 2026-08-12T18:50:30.053701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 33b4c1c4-53e8-4dea-bca2-5a01956d494f · outbound

This paper cites Growing echo-state network with multiple subreservoirs,.

Recurrent Stochastic Configuration Networks with Incremental Blocks Growing echo-state network with multiple subreservoirs,

Reference 19

Resolution
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raw_fallback, observed 2026-08-12T18:50:30.046176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation aed216f9-6750-47b3-8926-55025a5cbf47 · outbound

This paper cites Echo state networks: novel reservoir selection and hyperparameter optimization model for time series forecasting,.

Recurrent Stochastic Configuration Networks with Incremental Blocks Echo state networks: novel reservoir selection and hyperparameter optimization model for time series forecasting,

Reference 20

Resolution
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raw_fallback, observed 2026-08-12T18:50:30.038484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 855079e0-1168-48ce-812a-78e9a5bfa069 · outbound

This paper cites PSO-based growing echo state network,.

Recurrent Stochastic Configuration Networks with Incremental Blocks PSO-based growing echo state network,

Reference 21

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raw_fallback, observed 2026-08-12T18:50:30.031028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 5b1a93c7-df96-481a-af09-249ea63bb591 · outbound

This paper cites Parameterizing echo state networks for multi-step time series prediction,.

Recurrent Stochastic Configuration Networks with Incremental Blocks Parameterizing echo state networks for multi-step time series prediction,

Reference 22

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raw_fallback, observed 2026-08-12T18:50:30.023784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation ef982047-ed4a-4aa6-ab44-7abb9a49848c · outbound

This paper cites Editorial: randomized algorithms for training neural net- works,.

Recurrent Stochastic Configuration Networks with Incremental Blocks Editorial: randomized algorithms for training neural net- works,

Reference 23

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raw_fallback, observed 2026-08-12T18:50:30.016437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 525481af-b5dc-44df-945a-5b8f8d7c830a · outbound

This paper cites Insights into randomized algorithms for neural networks: practical issues and common pitfalls,.

Recurrent Stochastic Configuration Networks with Incremental Blocks Insights into randomized algorithms for neural networks: practical issues and common pitfalls,

Reference 24

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raw_fallback, observed 2026-08-12T18:50:30.009035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 5b13bd80-0ec4-4e76-b1ac-f0bbbb8fa093 · outbound

This paper cites Stochastic configuration networks: Fundamentals and algorithms,.

Recurrent Stochastic Configuration Networks with Incremental Blocks Stochastic configuration networks: Fundamentals and algorithms,

Reference 25

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no resolver link, observed 2026-08-12T18:50:29.936446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:50:29.936446Z digest=sha256:e9b8055fc96230f214e089c8cdc5389850c6a6cf6ed509934f1206b0f839a425

Observation 6ea63498-07dc-409d-86cb-b271fd269ec2 · outbound

This paper cites Recurrent Stochastic Configuration Networks for Temporal Data Analytics.

Recurrent Stochastic Configuration Networks with Incremental Blocks Recurrent Stochastic Configuration Networks for Temporal Data Analytics

Reference 26

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no resolver link, observed 2026-08-12T18:50:29.938863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:50:29.938863Z digest=sha256:c49172cdaa577ed4c5519c5843febb1ad16165f7d8970cca1b8252363ce80dfb

Observation a84a5bb5-28ed-4739-a7d3-2d1e084247e9 · outbound

This paper cites Adaptive filtering prediction and control,.

Recurrent Stochastic Configuration Networks with Incremental Blocks Adaptive filtering prediction and control,

Reference 27

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unresolved
no resolver link, observed 2026-08-12T18:50:29.941477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:50:29.941477Z digest=sha256:50d54b002e3e4245f481d199d8a0192b18550b6f1e4a0c814c7af88004c4eded

Observation 6b144a97-b75a-4a3e-859a-0b3363d5341c · outbound

This paper cites Stochastic configuration networks with block increments for data modeling in process industries,.

Recurrent Stochastic Configuration Networks with Incremental Blocks Stochastic configuration networks with block increments for data modeling in process industries,

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-12T18:50:29.994455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 59e2ec93-1053-44fe-ac40-15c1d94a3e41 · outbound

This paper cites Decoupled echo state networks with lateral inhibition,.

Recurrent Stochastic Configuration Networks with Incremental Blocks Decoupled echo state networks with lateral inhibition,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:50:29.987277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation a57fd4e7-3164-44db-9f7f-f33c962f89b3 · outbound

This paper cites Soft sensors for product quality monitoring in debutanizer distillation columns,.

Recurrent Stochastic Configuration Networks with Incremental Blocks Soft sensors for product quality monitoring in debutanizer distillation columns,

Reference 30

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no resolver link, observed 2026-08-12T18:50:29.948772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:50:29.948772Z digest=sha256:0f6da5664d18e5bcd3668b2f8dd5729cb2d2d506e7d69ca060a84a631e67ab87

Pith citing papers

Observation cb1f6e21-1823-4d82-894e-8e1db19aabd5 · inbound

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling cites this paper.

Recurrent Stochastic Configuration Networks with Hybrid Regularization for Nonlinear Dynamics Modelling Recurrent Stochastic Configuration Networks with Incremental Blocks

Reference 30

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local_arxiv, observed 2026-08-12T12:42:36.513085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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