Paper Citation Record · LEDGER

Training of Spiking Neural Networks with Expectation-Propagation

As of 17 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2506.23757.

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

pith.paper-citation-record.v1
2506.23757 v1

Coverage vector

measured 47 of 47 reference resolution

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One-hop event checks from named stored sources.

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Pith citing papers itemized under the disclosed page cap.

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

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Reference resolution

47 of 47 outbound references displayed

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External citation measurements

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Outbound references

Observation fe5cd538-37df-42f8-aa1c-631c69a327aa · outbound

This paper cites Networks of spiking neurons: the third generation of neural network models,.

Training of Spiking Neural Networks with Expectation-Propagation Networks of spiking neurons: the third generation of neural network models,

Reference 1

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This paper cites Deep learning in spiking neural networks,.

Training of Spiking Neural Networks with Expectation-Propagation Deep learning in spiking neural networks,

Reference 2

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This paper cites A review of learning in biologically plausible spiking neural networks,.

Training of Spiking Neural Networks with Expectation-Propagation A review of learning in biologically plausible spiking neural networks,

Reference 3

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This paper cites Memory and information processing in neuromorphic systems,.

Training of Spiking Neural Networks with Expectation-Propagation Memory and information processing in neuromorphic systems,

Reference 4

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Training of Spiking Neural Networks with Expectation-Propagation Unresolved cited work

Reference 5

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This paper cites Bio-inspired digit recognition using reward-modulated spike-timing-dependent plasticity in deep convolutional networks,.

Training of Spiking Neural Networks with Expectation-Propagation Bio-inspired digit recognition using reward-modulated spike-timing-dependent plasticity in deep convolutional networks,

Reference 6

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Observation b576939e-213c-47f1-bcc2-57b555fbd78d · outbound

This paper cites Spiking-yolo: spiking neural network for energy-efficient object detection,.

Training of Spiking Neural Networks with Expectation-Propagation Spiking-yolo: spiking neural network for energy-efficient object detection,

Reference 7

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Observation f9baa895-533d-4efb-b981-0cecb72cb370 · outbound

This paper cites Training a spiking neural network to control a 4-dof robotic arm based on spike timing-dependent plasticity,.

Training of Spiking Neural Networks with Expectation-Propagation Training a spiking neural network to control a 4-dof robotic arm based on spike timing-dependent plasticity,

Reference 8

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This paper cites Pose estimation and map formation with spiking neural networks: towards neuromorphic slam,.

Training of Spiking Neural Networks with Expectation-Propagation Pose estimation and map formation with spiking neural networks: towards neuromorphic slam,

Reference 9

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Observation b79713f9-22f0-4215-9e82-b8e300ecd6b5 · outbound

This paper cites Simultaneous localization and mapping for event-based vision systems,.

Training of Spiking Neural Networks with Expectation-Propagation Simultaneous localization and mapping for event-based vision systems,

Reference 10

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Observation 529d8222-2a2d-4306-91fa-0dbee5798a32 · outbound

This paper cites Conversion of continuous-valued deep networks to efficient event- driven networks for image classification,.

Training of Spiking Neural Networks with Expectation-Propagation Conversion of continuous-valued deep networks to efficient event- driven networks for image classification,

Reference 11

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Observation eef8b761-8bb1-44b1-bffb-c91575eef63d · outbound

This paper cites Real- time classification and sensor fusion with a spiking deep belief network,.

Training of Spiking Neural Networks with Expectation-Propagation Real- time classification and sensor fusion with a spiking deep belief network,

Reference 12

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Observation eb2d96ac-bf6e-4ab9-8bc8-0d20f24f4cce · outbound

This paper cites Fast- classifying, high-accuracy spiking deep networks through weight and threshold balancing,.

Training of Spiking Neural Networks with Expectation-Propagation Fast- classifying, high-accuracy spiking deep networks through weight and threshold balancing,

Reference 13

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Observation df77c658-e6ff-4a60-8d7a-94c41e0ac578 · outbound

This paper cites Going deeper in spiking neural networks: Vgg and residual architectures,.

Training of Spiking Neural Networks with Expectation-Propagation Going deeper in spiking neural networks: Vgg and residual architectures,

Reference 14

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Observation 3a648c50-deb0-486f-beec-d11b1a474c95 · outbound

This paper cites Surrogate gradient learning in spiking neural networks: Bringing the power of gradient-based optimization to spiking neural networks,.

Training of Spiking Neural Networks with Expectation-Propagation Surrogate gradient learning in spiking neural networks: Bringing the power of gradient-based optimization to spiking neural networks,

Reference 15

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Observation 2152b78b-a58e-4fef-ba0b-abc7f2f98f9b · outbound

This paper cites The remarkable robustness of surrogate gradient learning for instilling complex function in spiking neural networks,.

Training of Spiking Neural Networks with Expectation-Propagation The remarkable robustness of surrogate gradient learning for instilling complex function in spiking neural networks,

Reference 16

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Observation 4c7ee89e-53fd-4e0d-81fe-9b2d4322cbbd · outbound

This paper cites An introduction to probabilistic spiking neural networks: Probabilistic models, learning rules, and applications,.

Training of Spiking Neural Networks with Expectation-Propagation An introduction to probabilistic spiking neural networks: Probabilistic models, learning rules, and applications,

Reference 17

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Observation 1209c26b-43ca-44c8-b53b-ec929f29dd04 · outbound

This paper cites Matching recall and storage in sequence learning with spiking neural networks,.

Training of Spiking Neural Networks with Expectation-Propagation Matching recall and storage in sequence learning with spiking neural networks,

Reference 18

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This paper cites Noise as a resource for computation and learning in networks of spiking neurons,.

Training of Spiking Neural Networks with Expectation-Propagation Noise as a resource for computation and learning in networks of spiking neurons,

Reference 19

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This paper cites Lightweight probabilistic deep networks,.

Training of Spiking Neural Networks with Expectation-Propagation Lightweight probabilistic deep networks,

Reference 20

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This paper cites Bayesian continual learning via spiking neural networks,.

Training of Spiking Neural Networks with Expectation-Propagation Bayesian continual learning via spiking neural networks,

Reference 21

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Training of Spiking Neural Networks with Expectation-Propagation What uncertainties do we need in bayesian deep learning for computer vision?

Reference 22

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Training of Spiking Neural Networks with Expectation-Propagation A survey of uncertainty in deep neural networks,

Reference 23

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Training of Spiking Neural Networks with Expectation-Propagation Stochastic dynamics as a principle of brain function,

Reference 24

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This paper cites Neural dynamics as sampling: a model for stochastic computation in recurrent networks of spiking neurons,.

Training of Spiking Neural Networks with Expectation-Propagation Neural dynamics as sampling: a model for stochastic computation in recurrent networks of spiking neurons,

Reference 25

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This paper cites Bisnn: training spiking neural networks with binary weights via bayesian learning,.

Training of Spiking Neural Networks with Expectation-Propagation Bisnn: training spiking neural networks with binary weights via bayesian learning,

Reference 26

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This paper cites Expectation propagation for approximate Bayesian inference,.

Training of Spiking Neural Networks with Expectation-Propagation Expectation propagation for approximate Bayesian inference,

Reference 27

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Training of Spiking Neural Networks with Expectation-Propagation Unresolved cited work

Reference 28

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This paper cites Expectation propagation for neural networks with sparsity-promoting priors,.

Training of Spiking Neural Networks with Expectation-Propagation Expectation propagation for neural networks with sparsity-promoting priors,

Reference 29

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Training of Spiking Neural Networks with Expectation-Propagation Assumed density filtering methods for learning bayesian neural networks,

Reference 30

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This paper cites Probabilistic spiking neural networks training with expectation-propagation,.

Training of Spiking Neural Networks with Expectation-Propagation Probabilistic spiking neural networks training with expectation-propagation,

Reference 31

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This paper cites Expectation backpropagation: Parameter-free training of multilayer neural networks with continuous or discrete weights,.

Training of Spiking Neural Networks with Expectation-Propagation Expectation backpropagation: Parameter-free training of multilayer neural networks with continuous or discrete weights,

Reference 32

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This paper cites Probabilistic backpropagation for scalable learning of bayesian neural networks,.

Training of Spiking Neural Networks with Expectation-Propagation Probabilistic backpropagation for scalable learning of bayesian neural networks,

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Training of Spiking Neural Networks with Expectation-Propagation Stochastic expectation propagation,

Reference 34

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This paper cites Expectation propagation in the large data limit,.

Training of Spiking Neural Networks with Expectation-Propagation Expectation propagation in the large data limit,

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This paper cites Time structure of the activity in neural network models,.

Training of Spiking Neural Networks with Expectation-Propagation Time structure of the activity in neural network models,

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This paper cites Expectation propagation in linear regression models with spike-and- slab priors,.

Training of Spiking Neural Networks with Expectation-Propagation Expectation propagation in linear regression models with spike-and- slab priors,

Reference 37

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This paper cites Fast scalable image restoration using total variation priors and expectation propagation,.

Training of Spiking Neural Networks with Expectation-Propagation Fast scalable image restoration using total variation priors and expectation propagation,

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Training of Spiking Neural Networks with Expectation-Propagation On expectation propagation for generalised, linear and mixed models,

Reference 39

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This paper cites Semi-analytical approximations to statistical moments of sigmoid and softmax mappings of normal variables.

Training of Spiking Neural Networks with Expectation-Propagation Semi-analytical approximations to statistical moments of sigmoid and softmax mappings of normal variables

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Training of Spiking Neural Networks with Expectation-Propagation A family of algorithms for approximate bayesian inference,

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This paper cites Training spiking neural networks using lessons from deep learning,.

Training of Spiking Neural Networks with Expectation-Propagation Training spiking neural networks using lessons from deep learning,

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This paper cites The mnist database of handwritten digit images for machine learning research,.

Training of Spiking Neural Networks with Expectation-Propagation The mnist database of handwritten digit images for machine learning research,

Reference 43

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Training of Spiking Neural Networks with Expectation-Propagation Eliasmith and C

Reference 44

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Observation d66f80ef-7be9-4f38-a2ce-42468ffd716a · outbound

This paper cites Synaptic plasticity dynamics for deep continuous local learning (decolle),.

Training of Spiking Neural Networks with Expectation-Propagation Synaptic plasticity dynamics for deep continuous local learning (decolle),

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:37:52.415257Z

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Observation e2a62920-a939-44d4-b79f-fdf07bbd1a6d · outbound

This paper cites Computation with spikes in a winner-take-all network,.

Training of Spiking Neural Networks with Expectation-Propagation Computation with spikes in a winner-take-all network,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:37:52.242717Z

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Observation 348af8f5-cda7-432a-a75e-28c7eaaf5977 · outbound

This paper cites V owel: A local online learning rule for recurrent networks of probabilistic spiking winner- take-all circuits,.

Training of Spiking Neural Networks with Expectation-Propagation V owel: A local online learning rule for recurrent networks of probabilistic spiking winner- take-all circuits,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:37:52.115416Z

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Pith citing papers

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