Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks | Paper Citation Record

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This paper cites Stochastic resonance.Reviews of Modern Physics, 70:223–287, 1998.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Stochastic resonance.Reviews of Modern Physics, 70:223–287, 1998

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This paper cites Stochastic resonance and sensory information processing: a tutorial and review of application.Clinical Neurophysiology, 115(2):267–281, 2004.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Stochastic resonance and sensory information processing: a tutorial and review of application.Clinical Neurophysiology, 115(2):267–281, 2004

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This paper cites Fiete and H.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Fiete and H

Reference 3

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This paper cites Fiete, Michale S.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Fiete, Michale S

Reference 4

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This paper cites Probabilistic inference in general graphical models through sampling in stochastic networks of spiking neurons.PLoS Computational Biology, 7(12):e1002294, 2011.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Probabilistic inference in general graphical models through sampling in stochastic networks of spiking neurons.PLoS Computational Biology, 7(12):e1002294, 2011

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This paper cites Neural variability and sampling-based probabilistic representations in the visual cortex.Neuron, 92(2):530–543, 2016.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Neural variability and sampling-based probabilistic representations in the visual cortex.Neuron, 92(2):530–543, 2016

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This paper cites Aldo Faisal, Luc P.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Aldo Faisal, Luc P

Reference 7

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This paper cites McDonnell and Lawrence M.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks McDonnell and Lawrence M

Reference 8

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This paper cites Noise-modulated neural networks as an ap- plication of stochastic resonance.Neurocomputing, 277:29 – 37, 2018.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Noise-modulated neural networks as an ap- plication of stochastic resonance.Neurocomputing, 277:29 – 37, 2018

Reference 9

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This paper cites Noise-modulated neural networks for selectively functionalizing sub-networks by exploiting stochastic resonance.Neurocomputing, 448:1–9, 2021.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Noise-modulated neural networks for selectively functionalizing sub-networks by exploiting stochastic resonance.Neurocomputing, 448:1–9, 2021

Reference 10

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Observation 6509a9c3-6453-476d-a30e-cf16dc36a4db · outbound

This paper cites Spatial Partial Functionalization of Neural Networks based on Noise Fields.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Spatial Partial Functionalization of Neural Networks based on Noise Fields

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This paper cites Neftci, Hesham Mostafa, and Friedemann Zenke.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Neftci, Hesham Mostafa, and Friedemann Zenke

Reference 12

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This paper cites Neftci, Charles Augustine, Somnath Paul, and Georgios Detorakis.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Neftci, Charles Augustine, Somnath Paul, and Georgios Detorakis

Reference 13

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This paper cites Learning without feedback: Fixed random learning signals allow for feedforward training of deep neural networks.Frontiers in Neuroscience, 15, 2021.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Learning without feedback: Fixed random learning signals allow for feedforward training of deep neural networks.Frontiers in Neuroscience, 15, 2021

Reference 14

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This paper cites Lillicrap, Adam Santoro, Luke Marris, Colin J.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Lillicrap, Adam Santoro, Luke Marris, Colin J

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This paper cites The recent excitement about neural networks.Nature, 337:129–132, 1989.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks The recent excitement about neural networks.Nature, 337:129–132, 1989

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This paper cites Lillicrap, Daniel Cownden, Douglas B.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Lillicrap, Daniel Cownden, Douglas B

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Observation 044f14c0-1c40-4f6a-aceb-9cd3f1b14327 · outbound

This paper cites Direct feedback alignment provides learning in deep neural networks.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Direct feedback alignment provides learning in deep neural networks

Reference 18

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This paper cites Kolen and J.B.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Kolen and J.B

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This paper cites Humphreys, Timothy Lillicrap, and Douglas Tweed.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Humphreys, Timothy Lillicrap, and Douglas Tweed

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Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Unresolved cited work

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This paper cites The mechanism of stochastic resonance.Jour- nal of Physics A: Mathematical and general, 14:453–457, 1981.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks The mechanism of stochastic resonance.Jour- nal of Physics A: Mathematical and general, 14:453–457, 1981

Reference 22

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This paper cites Stochastic resonance in climatic change.Tellus, 34(1):10–15, 1982.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Stochastic resonance in climatic change.Tellus, 34(1):10–15, 1982

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Observation fa7e60a6-8d27-4422-a5a7-fb10552b6aa7 · outbound

This paper cites Stochastic resonance and the benefits of noise: from ice ages to crayfish and SQUIDs.Nature, 373(6509):33–36, 1995.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Stochastic resonance and the benefits of noise: from ice ages to crayfish and SQUIDs.Nature, 373(6509):33–36, 1995

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This paper cites What is stochastic resonance? definitions, misconceptions, debates, and its relevance to biology.PLoS Computational Biology, 5(5):e1000348, 2009.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks What is stochastic resonance? definitions, misconceptions, debates, and its relevance to biology.PLoS Computational Biology, 5(5):e1000348, 2009

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This paper cites Douglass, L.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Douglass, L

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This paper cites Levin and J.P.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Levin and J.P

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This paper cites Collins, Thomas T.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Collins, Thomas T

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This paper cites Interpreting neural response variability as monte carlo sampling of the posterior.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Interpreting neural response variability as monte carlo sampling of the posterior

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This paper cites Haefner, Pietro Berkes, and J´ ozsef Fiser.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Haefner, Pietro Berkes, and J´ ozsef Fiser

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Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Spontaneous cortical activity reveals hallmarks of an optimal internal model of the environment.Science, 331(6013):83–87, 2011

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Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Neural dynamics as sampling: A model for stochastic computation in recurrent networks of spiking neurons.PLOS Computational Biology, 7(11):e1002211, 2011

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Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Unresolved cited work

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Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Dropout: A simple way to prevent neural networks from overfitting.Journal of Machine Learning Research, 15(56):1929–1958, 2014

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Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Adding Gradient Noise Improves Learning for Very Deep Networks

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

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Networks of spiking neurons: The third generation of neural network models

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Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Training deep spiking neural networks using backpropagation.Frontiers in Neuroscience, 10, 2016

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This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

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Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Optimal spike-timing- dependent plasticity for precise action potential firing in supervised learning.Neural Computation, 18:1318–1348, 2006

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Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Stochastic variational learning in recurrent spiking networks.Frontiers in Computational Neuroscience, 8, 2014

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This paper cites Two routes to scalable credit assignment without weight symmetry.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Two routes to scalable credit assignment without weight symmetry

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This paper cites How Auto-Encoders Could Provide Credit Assignment in Deep Networks via Target Propagation.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks How Auto-Encoders Could Provide Credit Assignment in Deep Networks via Target Propagation

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Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Difference target propagation

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Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Towards scaling difference target propagation by learning backprop targets

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Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Equilibrium propagation: Bridging the gap between energy- based models and backpropagation.Frontiers in Computational Neuroscience, 11, 2017

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Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Whittington and Rafal Bogacz

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Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Leibo, and Tomaso Poggio

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Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Biologically-plausible learning algorithms can scale to large datasets

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Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Sebastian Seung

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Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Williams

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Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Gradients without Backpropagation

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Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Scaling forward gradient with local losses

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Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks The Forward-Forward Algorithm: Some Preliminary Investigations

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Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Error-driven input modulation: Solving the credit as- signment problem without a backward pass

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Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Training neural networks with local error signals

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This paper cites Greedy layerwise learning can scale to ImageNet.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Greedy layerwise learning can scale to ImageNet

Reference 58

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Observation 448ed162-7ba1-4229-ad0b-815d438f6a0f · outbound

This paper cites A solution to the learning dilemma for recurrent networks of spiking neurons.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks A solution to the learning dilemma for recurrent networks of spiking neurons

Reference 59

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Observation 23ff19f3-a10f-4641-9789-55710232ce35 · outbound

This paper cites On the stability and scalability of node perturbation learning.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks On the stability and scalability of node perturbation learning

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-01T14:54:29.099012Z

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Observation aa55eab0-d274-4955-a7de-e845f6e1f449 · outbound

This paper cites Assessing the scalability of biologically-motivated deep learning algorithms and architectures.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Assessing the scalability of biologically-motivated deep learning algorithms and architectures

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-01T14:54:29.278536Z

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Observation 79849949-7874-4525-8ba9-83004a435198 · outbound

This paper cites Feedback alignment in deep convolutional networks.

Reconstructing Backpropagation from Forward Fluctuations in Noise-modulated Neural Networks Feedback alignment in deep convolutional networks

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-01T14:54:29.398500Z

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