Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T14:30:33.231331Z
Paper Citation Record · LEDGER
A Neural Network Training Method Based on Neuron Connection Coefficient Adjustments
As of 12 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 1 inbound Pith citation observation for arXiv:2502.10414.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T15:48:43.180719Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-10T05:30:23.456663Z
Reference resolution
16 of 16 outbound references displayed
- verified exact1
- verified fuzzy14
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch1
External citation measurements
0
pith, observed 2026-08-10T05:30:23.456663Z
Outbound references
Observation c3ccc492-934b-4967-9c86-ccde5fa00271 · outbound
This paper cites Thi s process can be mathematically described by a set of differential equations [1].
A Neural Network Training Method Based on Neuron Connection Coefficient Adjustments Thi s process can be mathematically described by a set of differential equations [1]
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T14:30:33.420194Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 650e615f-5a34-4c40-8882-0452db1f3173 · outbound
This paper cites To enhance the biological interpretability of neural networks, many biologically inspired neural network models have been proposed.
A Neural Network Training Method Based on Neuron Connection Coefficient Adjustments To enhance the biological interpretability of neural networks, many biologically inspired neural network models have been proposed
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T14:30:33.409541Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 9a161c77-d806-4d72-8107-22d3923d5d0d · outbound
This paper cites In contrast, traditional neural networks lack inherent nonlinearit y and therefore rely on the explicit introduction of activation functions.
A Neural Network Training Method Based on Neuron Connection Coefficient Adjustments In contrast, traditional neural networks lack inherent nonlinearit y and therefore rely on the explicit introduction of activation functions
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T14:30:33.399765Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation ca592810-d356-4263-a83d-3f7b6ff66826 · outbound
This paper cites Within this network, we have incorporated connection coefficients between neurons for training, which bears a strong resemblance to traditional MLP architectures.
A Neural Network Training Method Based on Neuron Connection Coefficient Adjustments Within this network, we have incorporated connection coefficients between neurons for training, which bears a strong resemblance to traditional MLP architectures
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T14:30:33.390158Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation e490dd7e-0b8c-4311-b594-9744cd363bbd · outbound
This paper cites A quantitative description of membrane current and its application to conduction and excitation in nerve,.
A Neural Network Training Method Based on Neuron Connection Coefficient Adjustments A quantitative description of membrane current and its application to conduction and excitation in nerve,
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T14:30:33.381565Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 4f29cd46-6625-482e-9169-5df7735839c8 · outbound
This paper cites Multilayer f eedforward networks are universal approximators,.
A Neural Network Training Method Based on Neuron Connection Coefficient Adjustments Multilayer f eedforward networks are universal approximators,
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T14:30:33.372046Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 488f1819-6968-4e05-9421-f2dd5acba860 · outbound
This paper cites Cellular neural networks: Theory,.
A Neural Network Training Method Based on Neuron Connection Coefficient Adjustments Cellular neural networks: Theory,
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T14:30:33.362579Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation f130053e-432a-4470-bd34-1564d393c9c6 · outbound
This paper cites Chaotic neural networks,.
A Neural Network Training Method Based on Neuron Connection Coefficient Adjustments Chaotic neural networks,
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T14:30:33.352727Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation b6aac9e5-12e6-4ce5-a58a-626b6df67d1e · outbound
This paper cites Deep learning in spiking neural networks,.
A Neural Network Training Method Based on Neuron Connection Coefficient Adjustments Deep learning in spiking neural networks,
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T14:30:33.343199Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 9d11f264-de83-42b8-9c32-a2f1045b3e40 · outbound
This paper cites Survey of Security and Data Attacks on Machine Unlearning In Financial and E-Commerce.
A Neural Network Training Method Based on Neuron Connection Coefficient Adjustments Survey of Security and Data Attacks on Machine Unlearning In Financial and E-Commerce
Reference 10
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-10T14:30:33.276750Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 8eefb5e8-ab39-4c59-85ef-7579e68fc830 · outbound
This paper cites A Neural Network Training Method Based on Distributed PID Control.
A Neural Network Training Method Based on Neuron Connection Coefficient Adjustments A Neural Network Training Method Based on Distributed PID Control
Reference 11
- Resolution
- verified exact
- local_arxiv, observed 2026-08-10T14:30:33.261346Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation cf0493b8-8aa8-48f0-a588-b9014fb74597 · outbound
This paper cites Noriega, Multilayer perceptron tutorial (School of Computing, no.
A Neural Network Training Method Based on Neuron Connection Coefficient Adjustments Noriega, Multilayer perceptron tutorial (School of Computing, no
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T14:30:33.332976Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 5fb1edc7-11a5-4a96-aefb-f4075f9b4b62 · outbound
This paper cites Backpropagation: The basic theory,.
A Neural Network Training Method Based on Neuron Connection Coefficient Adjustments Backpropagation: The basic theory,
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T14:30:33.320868Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation b5dd28f2-50ca-4837-a1bd-d7143f76abf6 · outbound
This paper cites Liquid time-constant networks,.
A Neural Network Training Method Based on Neuron Connection Coefficient Adjustments Liquid time-constant networks,
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T14:30:33.308990Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 75c134ad-9222-43b3-95e6-a116b3a86687 · outbound
This paper cites Closed -form continuous -time neural networks,.
A Neural Network Training Method Based on Neuron Connection Coefficient Adjustments Closed -form continuous -time neural networks,
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T14:30:33.298638Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation dc44a394-a61f-47d6-abfb-695b6242a3fb · outbound
This paper cites Memristor bridge synapse -based neural network and its learning,.
A Neural Network Training Method Based on Neuron Connection Coefficient Adjustments Memristor bridge synapse -based neural network and its learning,
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T14:30:33.287605Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Pith citing papers
Observation 89aa14dc-9ab7-47ab-b944-a8d2fe57e408 · inbound
From Propagator to Oscillator: The Dual Role of Symmetric Differential Equations in Neural Systems cites this paper.
From Propagator to Oscillator: The Dual Role of Symmetric Differential Equations in Neural Systems A Neural Network Training Method Based on Neuron Connection Coefficient Adjustments
Reference 2025
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T15:48:43.405180Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.