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Paper Citation Record · LEDGER

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection

As of 9 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2506.06265.

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

pith.paper-citation-record.v1
2506.06265 v1

Coverage vector

measured 60 of 60 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T06:02:32.610495Z

measured 60 of 60 standing notices

One-hop event checks from named stored sources.

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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

60 of 60 outbound references displayed

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  • verified fuzzy32
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fbea6bf7-6ac1-48ea-bc63-2076306ba6b0 · outbound

This paper cites Breast Cancer Statistics.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Breast Cancer Statistics

Reference 1

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Observation bfa7d517-abca-434b-a02b-a7c46ced3ac3 · outbound

This paper cites an unresolved cited work.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Unresolved cited work

Reference 2

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Observation fc2c15be-e789-47ab-b0da-b960b5f93f75 · outbound

This paper cites Oncolytic virus-based combi- nation therapy in breast cancer.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Oncolytic virus-based combi- nation therapy in breast cancer

Reference 3

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Observation 1fbcd865-9043-4e88-83f4-f0606c767902 · outbound

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Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Unresolved cited work

Reference 4

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Observation 26489697-b9b4-4b3c-9e61-ad8b6b445abb · outbound

This paper cites SAFNet: A deep spa- tial attention network with classifier fusion for breast cancer detection.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection SAFNet: A deep spa- tial attention network with classifier fusion for breast cancer detection

Reference 5

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Observation e72f400a-ad52-4382-90d2-1cd8c9f1c3e9 · outbound

This paper cites Breast cancer: patho- genesis and treatments.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Breast cancer: patho- genesis and treatments

Reference 6

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Observation 97ce9f45-cd8e-4578-99ff-04247d71d334 · outbound

This paper cites Spiking Neural Network.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Spiking Neural Network

Reference 7

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Observation 9c339bcb-b2d3-4641-8131-205aa03aac2c · outbound

This paper cites Neural networks for computer-aided diagnosis in medicine: A review.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Neural networks for computer-aided diagnosis in medicine: A review

Reference 8

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Observation b7f7ef04-7e42-45a4-8513-8ba4433ffe41 · outbound

This paper cites Applicable artifi- cial intelligence for brain disease: A survey.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Applicable artifi- cial intelligence for brain disease: A survey

Reference 9

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Observation d7330670-9fe5-49d2-a9a6-24d10bf6a747 · outbound

This paper cites Backpropagation- Based Learning Techniques for Deep Spiking Neural Networks: A Sur- vey.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Backpropagation- Based Learning Techniques for Deep Spiking Neural Networks: A Sur- vey

Reference 10

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Observation fd6756bd-6b47-4781-9283-719f0d8f35bd · outbound

This paper cites Cluster analysis of breast cancer data using Genetic Algorithm and Spiking Neural Networks.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Cluster analysis of breast cancer data using Genetic Algorithm and Spiking Neural Networks

Reference 11

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Observation cbbaa285-518e-445b-b835-57cbfd4cdd5f · outbound

This paper cites Training Spiking Neural Networks with Metaheuristic Algorithms.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Training Spiking Neural Networks with Metaheuristic Algorithms

Reference 12

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Observation a21587da-7592-4ac5-ac46-f9909809cb92 · outbound

This paper cites Leveraging stochasticity in memris- tive synapses for efficient and reliable neuromorphic systems.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Leveraging stochasticity in memris- tive synapses for efficient and reliable neuromorphic systems

Reference 13

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Observation fc7c5578-3ef3-4e41-98ff-92a1969aab0a · outbound

This paper cites Breast Cancer Recognition Using Saliency-Based Spik- ing Neural Network.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Breast Cancer Recognition Using Saliency-Based Spik- ing Neural Network

Reference 14

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Observation eb4a5e17-c64b-4498-9dab-582c58295270 · outbound

This paper cites Effective multispike learning in a spiking neural network with a new temporal feedback backpropaga- tion for breast cancer detection.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Effective multispike learning in a spiking neural network with a new temporal feedback backpropaga- tion for breast cancer detection

Reference 15

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Observation 9aff3462-420b-42fd-ac06-63449fa6ab4e · outbound

This paper cites Spiking neural network reinforcement learning method based on temporal coding and STDP.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Spiking neural network reinforcement learning method based on temporal coding and STDP

Reference 16

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Observation a4abbea7-406d-4c20-8706-947eaff7f7cd · outbound

This paper cites Multi-stages attention breast cancer classification based on nonlinear spiking neural P neurons with autapses.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Multi-stages attention breast cancer classification based on nonlinear spiking neural P neurons with autapses

Reference 17

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Observation 97fde139-4734-418e-a031-26e4258d182c · outbound

This paper cites SWAT: A Spiking Neural Network Training Algorithm for Classification Problems.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection SWAT: A Spiking Neural Network Training Algorithm for Classification Problems

Reference 18

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Observation bb7aee0b-dd50-484a-b1d9-07168b18bc15 · outbound

This paper cites Nonlinear Spiking Neural Systems With Au- tapses for Predicting Chaotic Time Series.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Nonlinear Spiking Neural Systems With Au- tapses for Predicting Chaotic Time Series

Reference 19

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Observation 199d083f-d8ae-4ad4-89e9-3e341eb2effd · outbound

This paper cites DoB-SNN: A New Neuron Assembly-Inspired Spiking Neural Network for 21 Pattern Classification.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection DoB-SNN: A New Neuron Assembly-Inspired Spiking Neural Network for 21 Pattern Classification

Reference 20

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Observation ff3e49b1-f364-447e-a41c-8a681164f7cc · outbound

This paper cites On the complexity of finite sequences.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection On the complexity of finite sequences

Reference 21

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Observation b1800b51-f4da-477f-90b2-903b0bc76d73 · outbound

This paper cites Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems

Reference 22

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Observation 524f74ee-0684-490c-8e41-3527d6a1de1f · outbound

This paper cites A leaky integrate-and- fire model with adaptation for the generation of a spike train.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection A leaky integrate-and- fire model with adaptation for the generation of a spike train

Reference 23

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This paper cites Leaky Integrate and Fire Neuron by Charge-Discharge Dynamics in Floating-Body MOSFET.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Leaky Integrate and Fire Neuron by Charge-Discharge Dynamics in Floating-Body MOSFET

Reference 24

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This paper cites A generalized leaky integrate-and-fire neuron model with fast implementation method.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection A generalized leaky integrate-and-fire neuron model with fast implementation method

Reference 25

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Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Glif: A unified gated leaky integrate-and- fire neuron for spiking neural networks

Reference 26

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This paper cites Simulating leaky integrate-and-fire neuron with integers.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Simulating leaky integrate-and-fire neuron with integers

Reference 27

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Observation 80e0fa7d-85a8-41d2-9479-f5d1bf6c3115 · outbound

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Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection CLIF: Complementary Leaky Integrate-and-Fire Neuron for Spiking Neural Networks

Reference 28

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This paper cites Energy efficient neural codes.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Energy efficient neural codes

Reference 29

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Observation 9c756ea6-a1cf-4de1-b021-8b8b69547b6c · outbound

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Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Optimizing information pro- cessing in brain-inspired neural networks

Reference 30

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Observation 79cc4c33-9bcb-4676-a2d3-9810568dd197 · outbound

This paper cites Computational Intelligence and optimization techniques in commu- nications and control.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Computational Intelligence and optimization techniques in commu- nications and control

Reference 31

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Observation 1d59d923-9ece-4bb3-bf4d-615600e17e4e · outbound

This paper cites Does Adding of Neurons to the Network Layer Lead to Increased Transmission Efficiency? IEEE Access.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Does Adding of Neurons to the Network Layer Lead to Increased Transmission Efficiency? IEEE Access

Reference 32

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Observation 7ca3f8c6-91b9-4032-8f78-00fff68213d8 · outbound

This paper cites Stable Spike-Timing Dependent Plasticity Rule for Multilayer Unsupervised and Su- pervised Learning.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Stable Spike-Timing Dependent Plasticity Rule for Multilayer Unsupervised and Su- pervised Learning

Reference 33

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Observation 6ca10ad0-0ed4-4755-9435-71b9b9f02e78 · outbound

This paper cites Su- pervised Hebbian Learning.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Su- pervised Hebbian Learning

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 9463d848-0c26-4c42-918b-114f6feac321 · outbound

This paper cites Exploring Neuromorphic Com- puting Based on Spiking Neural Networks: Algorithms to Hardware.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Exploring Neuromorphic Com- puting Based on Spiking Neural Networks: Algorithms to Hardware

Reference 35

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 5c7c2460-6087-4f87-816d-37f0bfe8e91c · outbound

This paper cites In: Proceedings of the Image Analysis and Processing—ICIAP 2019; Sept 9–13, 2019; Trento, Italy.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection In: Proceedings of the Image Analysis and Processing—ICIAP 2019; Sept 9–13, 2019; Trento, Italy

Reference 36

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 8b7e4e59-21d6-4b00-9cb0-4478d5f6b97a · outbound

This paper cites A change of direction in pairwise neutrino conversion physics: The effect of collisions.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection A change of direction in pairwise neutrino conversion physics: The effect of collisions

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T06:02:32.534053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T06:02:32.534053Z digest=sha256:9a8a2ad39dd01db8f00d6a293ca7c87151b69232356d4fe96860f9e170c24c7c

Observation 4bbd7aff-4c1b-48d3-a819-a96e186cd46b · outbound

This paper cites an unresolved cited work.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Unresolved cited work

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T06:02:32.537904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T06:02:32.537904Z digest=sha256:778b4fcc728cc6b7903f7d19f1e0a6c67e3e94dc8fae9ddd35206a93e4ba260c

Observation bcbfd5ee-fcf3-4e49-8058-1267b8c33a22 · outbound

This paper cites Characterization of Gen- eralizability of Spike Timing Dependent Plasticity Trained Spiking Neural Networks.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Characterization of Gen- eralizability of Spike Timing Dependent Plasticity Trained Spiking Neural Networks

Reference 39

Resolution
metadata mismatch
raw_fallback, observed 2026-08-07T06:02:32.993911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T06:02:32.541302Z digest=sha256:d016c8b89313e8470f55e7bc36e4b13ad8112d571f8cfe477384c7b07b2b7eb6

Observation 29c43566-b207-48b4-8f14-42c140c30666 · outbound

This paper cites Spiking Neural Networks and Bio-Inspired Supervised Deep Learning: A Survey.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Spiking Neural Networks and Bio-Inspired Supervised Deep Learning: A Survey

Reference 40

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T06:02:32.544491Z digest=sha256:0b097ae61617130ebc0571f657a2a7516d09a6e3df05d3b1ba8ec457d7ed2a9d

Observation a708c536-ca65-413c-ae08-c7778facaeda · outbound

This paper cites Digital Twins: The New Frontier for Personalized Medicine? Appl Sci.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Digital Twins: The New Frontier for Personalized Medicine? Appl Sci

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:02:33.804903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T06:02:32.548263Z digest=sha256:580f569a8554ef5b12d63ade8eb8dd498dbb3bbb78490af4347703f0122ba1fc

Observation 88ab37c0-df95-44fc-98fb-675f5aca55df · outbound

This paper cites Artificial Neural Net- work (ANN) to Spiking Neural Network (SNN) Converters Based on Diffusive Memristors.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Artificial Neural Net- work (ANN) to Spiking Neural Network (SNN) Converters Based on Diffusive Memristors

Reference 42

Resolution
verified exact
doi, observed 2026-08-07T06:02:32.660286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T06:02:32.551496Z digest=sha256:50c309d7384df1c4bc9cd7c155f6036f3897c621a98f2b95de8200e1cc748d8b

Observation 7eaecc95-3482-42e3-b2e7-31832058b3a4 · outbound

This paper cites CS- QCFS: Bridging the performance gap in ultra-low latency spiking neural networks.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection CS- QCFS: Bridging the performance gap in ultra-low latency spiking neural networks

Reference 43

Resolution
metadata mismatch
raw_fallback, observed 2026-08-07T06:02:32.891777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T06:02:32.554637Z digest=sha256:0a646a8be8ddf16dc86226f9e45b07eaf56f3e55109e2cf462b76a7efe1e4d1b

Observation 9d0a8707-1ade-44e7-9c1c-9e633ee9ee25 · outbound

This paper cites Machine learning-based multiscale framework for mechanical behavior of nano-crystalline structures.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Machine learning-based multiscale framework for mechanical behavior of nano-crystalline structures

Reference 44

Resolution
metadata mismatch
raw_fallback, observed 2026-08-07T06:02:32.816830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T06:02:32.557879Z digest=sha256:aa6107a2129fa0a39cdc97bf03f501c39d836436a9d70a89a27e6814b0c64f40

Observation 5d7054e8-8b91-4d1a-9aa8-bdaa36a88ca3 · outbound

This paper cites Toward Evolving Neural Networks using Bio- Inspired Algorithms.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Toward Evolving Neural Networks using Bio- Inspired Algorithms

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:02:33.796434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T06:02:32.561623Z digest=sha256:62d3ee03080908e3741b6d508777e9393a3c382fae8a68d965c52fbb49e3cef9

Observation 47b7c119-6ba8-4c1c-be41-223a49c338cd · outbound

This paper cites Front Neurosci.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Front Neurosci

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:02:33.788670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T06:02:32.564925Z digest=sha256:f99027604aaca83c905a0107d51b7d5f240b263d74f10b9e015ec4d4573ad5c2

Observation 9aa46c4d-1836-4c62-8dec-5195ffd7c829 · outbound

This paper cites Effective Active Learning Method for Spiking Neural Networks.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Effective Active Learning Method for Spiking Neural Networks

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:02:33.780856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T06:02:32.568305Z digest=sha256:d02210e4106275b61638dbc1866ad8c75c4f6159d025338956bad4ad316f1d8d

Observation 16a91938-e414-449f-a3a7-32e2fb364d36 · outbound

This paper cites Learning representations by back- propagating errors.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Learning representations by back- propagating errors

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:02:33.772747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T06:02:32.571458Z digest=sha256:6a8941d5c620f31037748adf797498b5259f17a23031a78786a55fe9a7d87ebd

Observation 7ff61ed0-4443-4051-9bd3-1b9af496ad33 · outbound

This paper cites Back-propagation algorithm with variable adaptive momentum.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Back-propagation algorithm with variable adaptive momentum

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:02:33.764412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T06:02:32.574441Z digest=sha256:b5da3cdff18f4d18de6c85c322a2f41afb7165f9b564dc94c09f1f7bea0cd122

Observation 7cd9b6b3-3f12-484a-a23e-f17fdf117c7d · outbound

This paper cites The kinematics of the spike trains.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection The kinematics of the spike trains

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:02:33.756261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T06:02:32.577611Z digest=sha256:8395e442264d8e2b8c8ad0e2abf85ba79d066e4c1fdf327d655155e40ddf95fc

Observation 4775cfbb-70d3-4565-bcb5-aa392ade257d · outbound

This paper cites Analysis, classification, and coding of multielectrode spike trains with hidden Markov models.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Analysis, classification, and coding of multielectrode spike trains with hidden Markov models

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:02:33.748106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T06:02:32.580970Z digest=sha256:d6a8fbf78ac1211e7b80b3995239a96b67fe249df834971dff48ca5d6ae34642

Observation 607df9c2-9508-4ff6-ac02-41ce2ed6f8e8 · outbound

This paper cites Comprehensive Overview of Backpropagation Algorithm for Digital Image Denoising.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Comprehensive Overview of Backpropagation Algorithm for Digital Image Denoising

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:02:33.739525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T06:02:32.584103Z digest=sha256:633c84d65e6a8a8ead0d870d7670a6d39137882c9344dbf29045439ae7ce8081

Observation db751ecb-e939-4d39-b8d0-2be8e864aa7d · outbound

This paper cites Back propagation artificial neural network for diagnosis of heart disease.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Back propagation artificial neural network for diagnosis of heart disease

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:02:33.731102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T06:02:32.587372Z digest=sha256:3919453d369c8744ffc0a84fe7f715a4f68fbc42b9f1ed0a57506b99c42cfeb6

Observation 6d34d8d0-c0ae-4a24-9733-fc693a2ce143 · outbound

This paper cites The tempotron: a neuron that learns spike timing-based decisions.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection The tempotron: a neuron that learns spike timing-based decisions

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:02:33.722761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T06:02:32.590549Z digest=sha256:2c96ecd1ffd20c13dd1135bca2c66674b6c37ee185aab325d4d7e029a45017b0

Observation a602af53-d31d-4c08-ba3e-4d32c70d1067 · outbound

This paper cites A gradient learning rule for the tempotron.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection A gradient learning rule for the tempotron

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:02:33.713692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T06:02:32.593680Z digest=sha256:e782754dc975c977599c092111413c44e7aeb74048d3923a6fe99b24f074bb07

Observation 8f94e515-8246-44b0-9a99-914190877f1d · outbound

This paper cites A brain-inspired spiking neural network model with tem- poral encoding and learning.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection A brain-inspired spiking neural network model with tem- poral encoding and learning

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:02:33.704292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T06:02:32.597404Z digest=sha256:a797bc14f970ac7fc37506a5e8ea9a4b04ccb589f7084753dd348ad8798d05c2

Observation 471f0d9d-fbbb-4fa0-bb09-dd25db807376 · outbound

This paper cites An STDP training algorithm for a spiking neural network with dynamic threshold neurons.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection An STDP training algorithm for a spiking neural network with dynamic threshold neurons

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:02:33.695187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T06:02:32.600904Z digest=sha256:7c4dd40e05ad033b154014bc0c2146bebea3460e4bf0fe657b5bf6b922758d60

Observation 1ba7204b-ec0d-46e9-9c97-07951725a718 · outbound

This paper cites Solving a classifica- tion task by spiking neural network with STDP based on rate and temporal input encoding.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Solving a classifica- tion task by spiking neural network with STDP based on rate and temporal input encoding

Reference 58

Resolution
verified exact
doi, observed 2026-08-07T06:02:32.651601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T06:02:32.604064Z digest=sha256:9088f90f75c4704a35f8ee5e2b7fc96c85e1dc84a049574a97fff47d897ec973

Observation 07d8052d-62be-43b2-bf9e-b924d0b833f2 · outbound

This paper cites Devel- opment of a Self-Regulating Evolving Spiking Neural Network for classification problem.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Devel- opment of a Self-Regulating Evolving Spiking Neural Network for classification problem

Reference 59

Resolution
verified exact
doi, observed 2026-08-07T06:02:32.642475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T06:02:32.607046Z digest=sha256:1ec74cb99811f3f1158f0cef7d2bb0bca9828553a65d108cc0128321884b2d50

Observation 77a33a0a-9ad9-417c-b6cd-4a6979860dc9 · outbound

This paper cites Bio-Inspired Classification: Combining Information Theory and Spiking Neural Networks - Influ- ence of the Learning Rules.

Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection Bio-Inspired Classification: Combining Information Theory and Spiking Neural Networks - Influ- ence of the Learning Rules

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T06:02:33.685963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T06:02:32.610495Z digest=sha256:e827d5450792b25c431bc0380b9687d868dc5f5f1a34308919828b2094f450f3

Pith citing papers

No inbound Pith citation observations are available.