Paper Citation Record · LEDGER

Effective Training Principles of Physical Reservoirs

As of 22 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2606.10130.

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

pith.paper-citation-record.v1
2606.10130 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T15:10:36.729834Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

33 of 33 outbound references displayed

verified exact0
verified fuzzy0
unresolved32
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 09ef775d-e9d3-4501-93ba-ec87b7d624ab · outbound

This paper cites The unified Reservoir Computing concept and its digital hardware implementations,.

Effective Training Principles of Physical Reservoirs The unified Reservoir Computing concept and its digital hardware implementations,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation deb8194f-2611-4761-8c58-266325ae26ac · outbound

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

Effective Training Principles of Physical Reservoirs Reservoir computing approaches to recurrent neural network training,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 703079d3-646b-4652-b4ee-afcb49260017 · outbound

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

Effective Training Principles of Physical Reservoirs Real-time computing without stable states: A new framework for neural computation based on perturbations,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10b08de9-62dd-4ffc-8a88-9f314425b648 · outbound

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

Effective Training Principles of Physical Reservoirs Recent advances in physical reservoir computing: A review,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5fee8081-2c3f-4339-8ca1-9e40f6ceb1af · outbound

This paper cites Extreme learning machine: Theory and applications,.

Effective Training Principles of Physical Reservoirs Extreme learning machine: Theory and applications,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2700fbd6-22d5-41b2-9569-84d071c36f4d · outbound

This paper cites Robust forecasting using predictive generalized synchronization in reservoir computing,.

Effective Training Principles of Physical Reservoirs Robust forecasting using predictive generalized synchronization in reservoir computing,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb1fcd8e-287a-4af2-a6f9-8aadb1bdf5d5 · outbound

This paper cites Optimizing memory in reservoir computers,.

Effective Training Principles of Physical Reservoirs Optimizing memory in reservoir computers,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4596dec9-c03e-4d76-972d-d462e8287476 · outbound

This paper cites Embedding theory of reservoir computing and reducing reservoir network using time delays,.

Effective Training Principles of Physical Reservoirs Embedding theory of reservoir computing and reducing reservoir network using time delays,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c1be79e-e765-41c0-9ed9-3ecded938bf2 · outbound

This paper cites Stable output feedback in reservoir computing using ridge regression,.

Effective Training Principles of Physical Reservoirs Stable output feedback in reservoir computing using ridge regression,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1622a5a9-5ced-47fe-b714-9a93dcac089b · outbound

This paper cites Photonic extreme learning machine by free-space optical propagation,.

Effective Training Principles of Physical Reservoirs Photonic extreme learning machine by free-space optical propagation,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d1096e3-7049-44dc-bf0a-35b5fe482552 · outbound

This paper cites All-optical reservoir computing,.

Effective Training Principles of Physical Reservoirs All-optical reservoir computing,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90c89889-123d-4a28-9f55-7a0f0728f207 · outbound

This paper cites Multiplexed networks: reservoir computing with virtual and real nodes,.

Effective Training Principles of Physical Reservoirs Multiplexed networks: reservoir computing with virtual and real nodes,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 737f2eda-5a8b-4946-b5b6-287404e2d058 · outbound

This paper cites Reconfigurable semiconductor laser networks based on diffractive coupling,.

Effective Training Principles of Physical Reservoirs Reconfigurable semiconductor laser networks based on diffractive coupling,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 15892d1c-3800-4ab0-8c75-20e6fef8467e · outbound

This paper cites Neuromorphiccomputingviafission-basedbroadbandfrequencygeneration,.

Effective Training Principles of Physical Reservoirs Neuromorphiccomputingviafission-basedbroadbandfrequencygeneration,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 149a0717-63fa-4a0d-927f-f63d23f954c5 · outbound

This paper cites Principlesandmetricsofextremelearningmachinesusingahighlynonlinear fiber,.

Effective Training Principles of Physical Reservoirs Principlesandmetricsofextremelearningmachinesusingahighlynonlinear fiber,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec1ad545-8609-405f-a472-430fba1c3e8c · outbound

This paper cites Principlesandmetricsofextremelearningmachinesusingahighlynonlinear fiber,.

Effective Training Principles of Physical Reservoirs Principlesandmetricsofextremelearningmachinesusingahighlynonlinear fiber,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22c1ce19-7c97-4ac7-8c8e-996f642b6734 · outbound

This paper cites Robust regularized extreme learning machine for regression using iteratively reweighted least squares,.

Effective Training Principles of Physical Reservoirs Robust regularized extreme learning machine for regression using iteratively reweighted least squares,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7735174-c6be-4f39-a4e2-84c8e1a2791d · outbound

This paper cites Pruning and regularization in reservoir computing,.

Effective Training Principles of Physical Reservoirs Pruning and regularization in reservoir computing,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c678da7e-e275-4be4-9fd9-100535c961f7 · outbound

This paper cites Adding filters to improve reservoir computer performance,.

Effective Training Principles of Physical Reservoirs Adding filters to improve reservoir computer performance,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 187f4814-f304-4372-ab29-e01cc51c3fd8 · outbound

This paper cites Nonlinear inference capacity of fiber-optical extreme learning machines,.

Effective Training Principles of Physical Reservoirs Nonlinear inference capacity of fiber-optical extreme learning machines,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d62a6d43-92c4-4555-a4cc-983673e1f5aa · outbound

This paper cites On the partition of numbers,.

Effective Training Principles of Physical Reservoirs On the partition of numbers,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a5cef23-d57d-49ef-9e9b-f8878a062a18 · outbound

This paper cites An automatic method of solving discrete programming problems,.

Effective Training Principles of Physical Reservoirs An automatic method of solving discrete programming problems,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5bc90ecd-13a2-4407-b14c-96eb96cd33d2 · outbound

This paper cites Machine-aided near-transform-limited pulse compression in fully fiber-interconnected systems for efficient spectral broadening,.

Effective Training Principles of Physical Reservoirs Machine-aided near-transform-limited pulse compression in fully fiber-interconnected systems for efficient spectral broadening,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e59f282a-11b9-4476-bb0b-dce9e0080f46 · outbound

This paper cites Adaptive control of pulse phase in a chirped-pulse amplifier,.

Effective Training Principles of Physical Reservoirs Adaptive control of pulse phase in a chirped-pulse amplifier,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67946e52-222b-43ec-b242-ce4ef8ee5ac0 · outbound

This paper cites Real-time reservoir computing network-based systems for detection tasks on visual contents,.

Effective Training Principles of Physical Reservoirs Real-time reservoir computing network-based systems for detection tasks on visual contents,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18374405-4992-4421-8274-c05d01d3d9c6 · outbound

This paper cites A multicriteria approach to find predictive and sparse models with stable feature selection for high-dimensional data,.

Effective Training Principles of Physical Reservoirs A multicriteria approach to find predictive and sparse models with stable feature selection for high-dimensional data,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42026001-27ff-44bf-959c-9663eba2f4ee · outbound

This paper cites Sensitivity-guided framework for pruned and quantized reservoir computing accelerators,.

Effective Training Principles of Physical Reservoirs Sensitivity-guided framework for pruned and quantized reservoir computing accelerators,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 358f0f11-3cf4-4c3b-bf56-e35c0dd870bf · outbound

This paper cites A comprehensive study of random forest for short-term load forecasting,.

Effective Training Principles of Physical Reservoirs A comprehensive study of random forest for short-term load forecasting,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4e7a2d3-6773-4c57-b952-c808da4a2574 · outbound

This paper cites Random forest-driven photonic reservoir computing model for signal modulation recognition,.

Effective Training Principles of Physical Reservoirs Random forest-driven photonic reservoir computing model for signal modulation recognition,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 424ec378-21db-4c82-b848-e69a03e4029f · outbound

This paper cites SVM–ELM: Pruning of extreme learning machine with support vector machines for regression,.

Effective Training Principles of Physical Reservoirs SVM–ELM: Pruning of extreme learning machine with support vector machines for regression,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c5de03d-e7d8-41f8-8432-e8ca517deeab · outbound

This paper cites OP-ELM: Optimally pruned extreme learning machine,.

Effective Training Principles of Physical Reservoirs OP-ELM: Optimally pruned extreme learning machine,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27ed50de-31d0-435f-a4a0-4b7c203ca200 · outbound

This paper cites Novel and efficient randomized algorithms for feature selection,.

Effective Training Principles of Physical Reservoirs Novel and efficient randomized algorithms for feature selection,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-06-27T15:10:36.729834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b600e6b-25cd-4788-b4c9-8b2a1a86c4bb · outbound

This paper cites Hoerl and Robert W.

Effective Training Principles of Physical Reservoirs Hoerl and Robert W

Reference 34

Resolution: metadata mismatch; arxiv_id, observed 2026-06-27T15:10:59.358747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

No inbound Pith citation observations are available.