Dan F. M. Goodman

According to our database, Dan F. M. Goodman authored at least 22 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Nonlinear fusion is optimal for a wide class of multisensory tasks.

Marcus Ghosh, Gabriel Béna, Volker Bormuth, Dan F. M. Goodman

PLoS Comput. Biol., 2024

Adapting to time: why nature evolved a diverse set of neurons.

Karim Habashy, Benjamin D. Evans, Dan F. M. Goodman, Jeffrey S. Bowers

CoRR, 2024

2023

Spiking Network Initialisation and Firing Rate Collapse.

Nicolas Perez Nieves, Dan F. M. Goodman

CoRR, 2023

2021

Further Towards Unambiguous Edge Bundling: Investigating Power-Confluent Drawings for Network Visualization.

Jonathan X. Zheng, Samraat Pawar, Dan F. M. Goodman

IEEE Trans. Vis. Comput. Graph., 2021

Extreme sparsity gives rise to functional specialization.

Gabriel Béna, Dan F. M. Goodman

CoRR, 2021

Sparse Spiking Gradient Descent.

Nicolas Perez Nieves, Dan F. M. Goodman

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2019

Graph Drawing by Stochastic Gradient Descent.

Jonathan X. Zheng, Samraat Pawar, Dan F. M. Goodman

IEEE Trans. Vis. Comput. Graph., 2019

2018

Code Generation in Computational Neuroscience: A Review of Tools and Techniques.

Inga Blundell, Romain Brette, Thomas A. Cleland, Thomas G. Close, Daniel Coca, Andrew P. Davison, Sandra Diaz-Pier, Carlos Fernandez Musoles, Padraig Gleeson, Dan F. M. Goodman, Michael L. Hines, Michael W. Hopkins, Pramod S. Kumbhar, David R. Lester, Bóris Marin, Abigail Morrison, Eric Müller, Thomas Nowotny, Alexander Peyser, Dimitri Plotnikov, Paul Richmond, Andrew Rowley, Bernhard Rumpe, Marcel Stimberg, Alan B. Stokes, Adam R. Tomkins, Guido Trensch, Michael Marmaduke Woodman, Jochen Martin Eppler

Frontiers Neuroinformatics, 2018

Comments on "Towards Unambiguous Edge Bundling: Investigating Confluent Drawings for Network Visualization".

Jonathan X. Zheng, Samraat Pawar, Dan F. M. Goodman

CoRR, 2018

2017

Graph Drawing by Weighted Constraint Relaxation.

Jonathan X. Zheng, Dan F. M. Goodman, Samraat Pawar

CoRR, 2017

2014

Brian Spiking Neural Network Simulator.

Dan F. M. Goodman, Romain Brette

Proceedings of the Encyclopedia of Computational Neuroscience, 2014

High-Dimensional Cluster Analysis with the Masked EM Algorithm.

Shabnam N. Kadir, Dan F. M. Goodman, Kenneth D. Harris

Neural Comput., 2014

Equation-oriented specification of neural models for simulations.

Marcel Stimberg, Dan F. M. Goodman, Victor Benichoux, Romain Brette

Frontiers Neuroinformatics, 2014

2013

Brian simulator.

Dan F. M. Goodman, Romain Brette

Scholarpedia, 2013

Playdoh: A lightweight Python library for distributed computing and optimisation.

Cyrille Rossant, Bertrand Fontaine, Dan F. M. Goodman

J. Comput. Sci., 2013

2011

Vectorized Algorithms for Spiking Neural Network Simulation.

Romain Brette, Dan F. M. Goodman

Neural Comput., 2011

Brian Hears: Online Auditory Processing Using Vectorization Over Channels.

Bertrand Fontaine, Dan F. M. Goodman, Victor Benichoux, Romain Brette

Frontiers Neuroinformatics, 2011

2010

Spike-Timing-Based Computation in Sound Localization.

Dan F. M. Goodman, Romain Brette

PLoS Comput. Biol., 2010

Code Generation: A Strategy for Neural Network Simulators.

Dan F. M. Goodman

Neuroinformatics, 2010

Automatic fitting of spiking neuron models to electrophysiological recordings.

Cyrille Rossant, Dan F. M. Goodman, Jonathan Platkiewicz, Romain Brette

Frontiers Neuroinformatics, 2010

Learning to localise sounds with spiking neural networks.

Dan F. M. Goodman, Romain Brette

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2008

Brian: a simulator for spiking neural networks in Python.

Dan F. M. Goodman, Romain Brette

Frontiers Neuroinformatics, 2008