Category: Machine learning
Related organisations
Inclusive networking and education for neuroscience.
Organisation for neuroscientists interested in spiking neural networks.
Related software
Python package for psychophysical tests of automatic speech recognition systems.
Spike sorting.
Graph layout using stochastic gradient descent.
Related videos
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Nonlinearity and network topology in multimodal circuitsTalk / 2024
Marcus Ghosh talk at ICNS -
Brain Inspired interviewInterview / 2024
Dan Goodman interview on Brain Inspired podcast -
The Psychometrics of Automatic Speech RecognitionTalk / 2022
Talk on applying psychometric testing to automatic speech recognition systems. -
Cosyne tutorial on spiking neural networks (2/2)Tutorial / 2022
Part 2 - (Machine) learning with SNNs -
Cosyne tutorial on spiking neural networks (1/2)Tutorial / 2022
Part 1 - "Classical" SNNs -
Understanding the role of neural heterogeneity in learningTalk / 2021
Talk on neural heterogeneity by Nicolas Perez. -
Neural heterogeneity promotes robust learningTalk / 2021
Talk on neural heterogeneity by Dan Goodman.
Related publications
2024
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Habashy KG, Evans BD, Goodman DFM, Bowers JS (2024)
Adapting to time: why nature may have evolved a diverse set of neurons.
PLoS Computational Biology -
Ghosh M, et al.
Spiking neural network models of sound localisation via a massively collaborative process.
Preprint
2023
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Perez N (2023)
Robust and efficient training on deep spiking neural networks.
PhD thesis, Imperial College London
2022
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Goodman D, Fiers T, Gao R, Ghosh M, Perez N (2022)
Spiking Neural Network Models in Neuroscience - Cosyne Tutorial 2022.
Zenodo -
Weerts L, Rosen S, Clopath C, Goodman DFM
The Psychometrics of Automatic Speech Recognition.
Preprint
2021
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Perez-Nieves N, Goodman DFM (2021)
Sparse spiking gradient descent.
Advances in Neural Information Processing Systems -
Perez-Nieves N, Leung VCH, Dragotti PL, Goodman DFM (2021)
Neural heterogeneity promotes robust learning.
Nature Communications -
Engel I (2021)
Improving binaural audio techniques for augmented reality.
PhD thesis, Imperial College London -
Achakulvisut T, et al. (2021)
Towards democratizing and automating online conferences: lessons from the Neuromatch conferences.
Trends in Cognitive Sciences -
Zenke F, et al. (2021)
Visualizing a joint future of neuroscience and neuromorphic engineering.
Neuron -
Weerts L (2021)
Features of hearing: applications of machine learning to uncover the building blocks of hearing.
PhD thesis, Imperial College London -
Zheng JX (2021)
Advances in network visualisation with an application to serious games.
PhD thesis, Imperial College London
2020
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Achakulvisut T, Ruangrong T, Acuna DE, Wyble B, Goodman D, Kording K (2020)
neuromatch: Algorithms to match scientists.
eLife Labs -
Achakulvisut T, et al. (2020)
Point of View: Improving on legacy conferences by moving online.
eLife -
Hathway P (2020)
Biologically-inspired machine learning approaches to large-scale neural data analysis.
PhD thesis, Imperial College London
2019
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Chu Y, Goodman DFM (2019)
An Inference Network Model for Goal-directed Attentional Selection.
Cognitive Computational Neuroscience -
Weerts L, Clopath C, Goodman DFM (2019)
A Unifying Framework for Neuro-Inspired, Data-Driven Detection of Low-Level Auditory Features.
Cognitive Computational Neuroscience -
Perez-Nieves N, Leung VCH, Dragotti PL, Goodman DFM (2019)
Advantages of heterogeneity of parameters in spiking neural network training.
Cognitive Computational Neuroscience - + 4 conference papers
2018
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Zheng JX, Pawar S, Goodman DFM (2018)
Confluent* Drawings by Hierarchical Clustering.
Graph Drawing and Network Visualization -
Zheng JX, Pawar S, Goodman DFM (2018)
Graph Drawing by Stochastic Gradient Descent.
IEEE Transactions on Visualization and Computer Graphics - + 1 conference paper
2016
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Rossant C, et al. (2016)
Spike sorting for large, dense electrode arrays.
Nature Neuroscience
2014
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Kadir SN, Goodman DFM, Harris KD (2014)
High-dimensional cluster analysis with the masked EM algorithm.
Neural Computation
2013
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Goodman DFM, Benichoux V, Brette R (2013)
Decoding neural responses to temporal cues for sound localization.
eLife