Paper Citation Record · LEDGER

Continuous signal sparse encoding using analog neuromorphic variability

As of 21 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2501.13504.

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

pith.paper-citation-record.v1
2501.13504 v2

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:56:09.129774Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

32 of 32 outbound references displayed

verified exact0
verified fuzzy30
unresolved2
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 18fc87d3-1bdf-4205-8cce-4fcd4437af5a · outbound

This paper cites Pattern recognition computation using action potential timing for stimulus representation.

Continuous signal sparse encoding using analog neuromorphic variability Pattern recognition computation using action potential timing for stimulus representation

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.513379Z

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Observation 4e50d917-6273-4a98-88d4-cc6b97eae63d · outbound

This paper cites Manipulating synthetic opto- genetic odors reveals the coding logic of olfac- tory perception.

Continuous signal sparse encoding using analog neuromorphic variability Manipulating synthetic opto- genetic odors reveals the coding logic of olfac- tory perception

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.501684Z

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Observation 1c146d11-45c9-4680-b4f3-656c55e0124b · outbound

This paper cites Efficient coding in heterogeneous neuronal populations.

Continuous signal sparse encoding using analog neuromorphic variability Efficient coding in heterogeneous neuronal populations

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.489019Z

Source-reported events for the cited work

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Observation 264533e7-4a6b-45e6-839c-223926e31300 · outbound

This paper cites Adapting to time: Why nature may have evolved a diverse set of neurons.

Continuous signal sparse encoding using analog neuromorphic variability Adapting to time: Why nature may have evolved a diverse set of neurons

Reference 4

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Source-reported events for the cited work

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Observation cbca36f9-401d-44d7-a630-0113a6fc977f · outbound

This paper cites Reliability of spike timing in neocortical neurons.

Continuous signal sparse encoding using analog neuromorphic variability Reliability of spike timing in neocortical neurons

Reference 5

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Source-reported events for the cited work

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Observation fc75e7c4-a9b9-4f4f-b146-606a9016809f · outbound

This paper cites Gating of sensory input by spontaneous cortical activity.

Continuous signal sparse encoding using analog neuromorphic variability Gating of sensory input by spontaneous cortical activity

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.469277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1e471a78-7c94-4591-a54b-83ed9b34e248 · outbound

This paper cites Packet-based communication in the cortex.

Continuous signal sparse encoding using analog neuromorphic variability Packet-based communication in the cortex

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.458211Z

Source-reported events for the cited work

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Observation f050b7f7-57b9-4b34-ac66-10e149959a31 · outbound

This paper cites Backbone spiking sequence as a basis for preplay, replay, and default states in human cortex.

Continuous signal sparse encoding using analog neuromorphic variability Backbone spiking sequence as a basis for preplay, replay, and default states in human cortex

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.446575Z

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Observation 64deddb2-7b00-4c7f-bf14-fd675f7ca2c4 · outbound

This paper cites Neuronal sequences in population bursts encode information in human cortex.

Continuous signal sparse encoding using analog neuromorphic variability Neuronal sequences in population bursts encode information in human cortex

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.434026Z

Source-reported events for the cited work

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Observation 034baead-4c52-4f4d-8e1c-1ed595bd9e21 · outbound

This paper cites Neural heterogeneity promotes robust learning.

Continuous signal sparse encoding using analog neuromorphic variability Neural heterogeneity promotes robust learning

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.421783Z

Source-reported events for the cited work

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Observation 8f142a9b-eda8-43e2-8016-0aa19dad87cf · outbound

This paper cites Sequence approximation us- ing feedforward spiking neural network for spa- tiotemporal learning: Theory and optimiza- tion methods.

Continuous signal sparse encoding using analog neuromorphic variability Sequence approximation us- ing feedforward spiking neural network for spa- tiotemporal learning: Theory and optimiza- tion methods

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.410015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8bb7e116-5046-4f51-8202-cf1ebc6c02b9 · outbound

This paper cites Neural heterogeneity controls computa- tions in spiking neural networks.

Continuous signal sparse encoding using analog neuromorphic variability Neural heterogeneity controls computa- tions in spiking neural networks

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.399661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c7103a23-0aba-4ad0-997c-6f34157d80f0 · outbound

This paper cites Efficient and robust coding in het- erogeneous recurrent networks.

Continuous signal sparse encoding using analog neuromorphic variability Efficient and robust coding in het- erogeneous recurrent networks

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.389835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4dd8e1df-4d0d-4fc3-964a-1f66c84fe531 · outbound

This paper cites Bayesian population decoding of spiking neurons.

Continuous signal sparse encoding using analog neuromorphic variability Bayesian population decoding of spiking neurons

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.379156Z

Source-reported events for the cited work

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Observation 73a659dd-48d2-4884-8923-b971d522fb4b · outbound

This paper cites Time encoding with an integrate- and-fire neuron with a refractory period.

Continuous signal sparse encoding using analog neuromorphic variability Time encoding with an integrate- and-fire neuron with a refractory period

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.367927Z

Source-reported events for the cited work

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Observation 1f168e26-f636-4871-9845-a7accba9ff83 · outbound

This paper cites Reconstruction of sensory stimuli encoded with integrate-and-fire neurons with random thresholds.

Continuous signal sparse encoding using analog neuromorphic variability Reconstruction of sensory stimuli encoded with integrate-and-fire neurons with random thresholds

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.355447Z

Source-reported events for the cited work

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Observation e992f56f-9dff-4dd9-95f2-9c1976295f67 · outbound

This paper cites Sampling and reconstruction of ban- dlimited signals with multi-channel time encod- ing.

Continuous signal sparse encoding using analog neuromorphic variability Sampling and reconstruction of ban- dlimited signals with multi-channel time encod- ing

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.344180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c668ba40-9142-47c6-b617-bf2ff4a5e4a1 · outbound

This paper cites Bsa, a fast and accurate spike train encoding scheme.

Continuous signal sparse encoding using analog neuromorphic variability Bsa, a fast and accurate spike train encoding scheme

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.332851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c2926a4b-ee63-466b-b3d0-339a8929546c · outbound

This paper cites Dynamical encoding by networks of competing neuron groups: winnerless competition.

Continuous signal sparse encoding using analog neuromorphic variability Dynamical encoding by networks of competing neuron groups: winnerless competition

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.319340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 114d5c3f-9212-4fbc-ac2a-f217514083c3 · outbound

This paper cites Temporal information transformed into a spa- tial code by a neural network with realis- tic properties.

Continuous signal sparse encoding using analog neuromorphic variability Temporal information transformed into a spa- tial code by a neural network with realis- tic properties

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.309608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6fe87099-60d5-416d-852f-05d6aa6333ef · outbound

This paper cites High-performance deep spiking neural networks with 0.3 spikes per neuron.

Continuous signal sparse encoding using analog neuromorphic variability High-performance deep spiking neural networks with 0.3 spikes per neuron

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.300251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 37b1e694-2829-4480-83da-03858a9d30ac · outbound

This paper cites Fast and energy-efficient neuromorphic deep learning with first-spike times.

Continuous signal sparse encoding using analog neuromorphic variability Fast and energy-efficient neuromorphic deep learning with first-spike times

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.289930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e1f70c30-fe04-44f7-9a27-90e00374fd2d · outbound

This paper cites Effi- cient codes and balanced networks.

Continuous signal sparse encoding using analog neuromorphic variability Effi- cient codes and balanced networks

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.277295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c062d84e-ceab-423e-b962-3bd09e0f11c7 · outbound

This paper cites Predictive coding of dynamical variables in balanced spiking networks.

Continuous signal sparse encoding using analog neuromorphic variability Predictive coding of dynamical variables in balanced spiking networks

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.264751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0c3a0c9f-e60b-47ef-93f7-933b9067e85c · outbound

This paper cites Ro- bust computation with rhythmic spike patterns.

Continuous signal sparse encoding using analog neuromorphic variability Ro- bust computation with rhythmic spike patterns

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.253694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9f959a55-d49b-4d26-8336-64794d60653f · outbound

This paper cites Extended liquid state machines for speech recognition.

Continuous signal sparse encoding using analog neuromorphic variability Extended liquid state machines for speech recognition

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.241901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 97da51fd-a7aa-45bc-86ec-8131aeb253b8 · outbound

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

Continuous signal sparse encoding using analog neuromorphic variability Real-time computing without stable states: A new framework for neural computation based on perturbations

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.230611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6127dee3-33e5-4329-91ae-aeb4fd111012 · outbound

This paper cites A scalable multicore architec- ture with heterogeneous memory structures for dynamic neuromorphic asynchronous proces- sors (dynaps).

Continuous signal sparse encoding using analog neuromorphic variability A scalable multicore architec- ture with heterogeneous memory structures for dynamic neuromorphic asynchronous proces- sors (dynaps)

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.219147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9d321b2e-ff66-4bc2-80f3-565c384f1d5e · outbound

This paper cites Brain-inspired methods for achieving robust computation in heteroge- neous mixed-signal neuromorphic processing systems.

Continuous signal sparse encoding using analog neuromorphic variability Brain-inspired methods for achieving robust computation in heteroge- neous mixed-signal neuromorphic processing systems

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.207575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d98f47f4-5a4f-4b7e-9be0-16f5d28aaca5 · outbound

This paper cites First-spike latency information in single neurons increases when referenced to population onset.

Continuous signal sparse encoding using analog neuromorphic variability First-spike latency information in single neurons increases when referenced to population onset

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.197212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a8b45b40-5ea2-44d6-8636-d2347875f0f2 · outbound

This paper cites Robust compression and detection of epileptiform patterns in ecog using a real-time spiking neural network hardware framework.

Continuous signal sparse encoding using analog neuromorphic variability Robust compression and detection of epileptiform patterns in ecog using a real-time spiking neural network hardware framework

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.186532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation bccfba99-569a-43ae-b769-8c0e8287b622 · outbound

This paper cites Neuromor- phic electronic circuits for building autonomous cognitive systems.

Continuous signal sparse encoding using analog neuromorphic variability Neuromor- phic electronic circuits for building autonomous cognitive systems

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:56:09.175233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

No inbound Pith citation observations are available.