Sander Bohte

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Joost KokVice-Dean Mathematics and Computer ScienceVerified email at tue.nl
Pieter RoelfsemaVerified email at nin.knaw.nl
Cornelis W. OosterleeUtrecht University, Mathematical InstituteVerified email at uu.nl
Bojian YinEindhoven University of TechnologyVerified email at tue.nl
HS ScholteDepartment of Brain & Cognition, University of AmsterdamVerified email at uva.nl
Enrico GerdingUniversity of SouthamptonVerified email at ecs.soton.ac.uk
Davide ZambranoIndoor Sports - SportradarVerified email at sportradar.com
Jaldert RomboutsVicariousVerified email at vicarious.com
Cyriel PennartzHoogleraar Cognitie & Neurowetenschappen, Univ. van AmsterdamVerified email at uva.nl
Anastasia BorovykhAssistant Professor Imperial College LondonVerified email at imperial.ac.uk
Federico CorradiEindhoven University of TechnologyVerified email at tue.nl
Shirin DoraLoughborough UniversityVerified email at lboro.ac.uk
Paugam-MoisyProfesseur d'InformatiqueVerified email at lri.fr
Isabella PozziCentrum Wiskunde & Informatica, Netherlands Institute for NeuroscienceVerified email at cwi.nl
Michael MozerGoogle DeepMind; University of ColoradoVerified email at colorado.edu
Marcel van GervenProfessor of Artificial Cognitive Systems, Donders Institute for Brain, Cognition and BehaviourVerified email at donders.ru.nl
Lynn K. A. SörensenMassachusetts Institute of TechnologyVerified email at mit.edu
Nikolaj Takata MückePostdoc, Centrum Wiskunde & InformaticaVerified email at cwi.nl
Edward de HaanDonders Institute, Radboud UniversityVerified email at uva.nl
Heleen SlagterProfessor of Cognitive Neuroscience, Vrije Universiteit AmsterdamVerified email at vu.nl

Sander Bohte

CWI Amsterdam

Verified email at cwi.nl - Homepage

Spiking Neural Networks Biologically Plausible Deep Learning Deep Reinforcement Learning


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Error-backpropagation in temporally encoded networks of spiking neurons SM Bohte, JN Kok, H La Poutre Neurocomputing 48 (1), 17-37, 2002	1457*	2002
Conditional time series forecasting with convolutional neural networks A Borovykh, S Bohte, CW Oosterlee arXiv preprint arXiv:1703.04691, 2017	667	2017
Handbook of natural computing T Bäck, JN Kok, G Rozenberg Springer, Heidelberg, 2012	557	2012
Artificial neural networks as models of neural information processing M Van Gerven, S Bohte Frontiers in Computational Neuroscience 11, 114, 2017	519	2017
Computing with spiking neuron networks H Paugam-Moisy, S Bohte Handbook of Natural Computing, 40p. Springer, Heidelberg, 2009	414	2009
Unsupervised clustering with spiking neurons by sparse temporal coding and multilayer RBF networks SM Bohte, H La Poutré, JN Kok IEEE Transactions on neural networks 13 (2), 426-435, 2002	303	2002
The evidence for neural information processing with precise spike-times: A survey SM Bohte Natural Computing 3, 195-206, 2004	218	2004
Accurate and efficient time-domain classification with adaptive spiking recurrent neural networks B Yin, F Corradi, SM Bohté Nature Machine Intelligence 3 (10), 905-913, 2021	200	2021
Adaptive resource allocation for efficient patient scheduling IB Vermeulen, SM Bohte, SG Elkhuizen, H Lameris, PJM Bakker, ... Artificial intelligence in medicine 46 (1), 67-80, 2009	179	2009
Pricing options and computing implied volatilities using neural networks S Liu, CW Oosterlee, SM Bohte Risks 7 (1), 16, 2019	167	2019
Method and system for automated marketing of attention area content L Poutre, J Antonius, SM Bohte, EH Gerding, FW Bomhof, J Jonker, ... US Patent App. 20,030/018,539, 2002	166	2002
Sparse computation in adaptive spiking neural networks D Zambrano, R Nusselder, HS Scholte, SM Bohté Frontiers in neuroscience 12, 987, 2019	133*	2019
Dilated convolutional neural networks for time series forecasting A Borovykh, S Bohte, CW Oosterlee Journal of Computational Finance 29, 73-101, 2018	129	2018
Spiking neural networks: Principles and challenges. A Grüning, SM Bohte ESANN, 2014	116	2014
Effective and efficient computation with multiple-timescale spiking recurrent neural networks B Yin, F Corradi, SM Bohté International Conference on Neuromorphic Systems 2020, 1-8, 2020	112	2020
Spike-prop: error-backpropagation in multi-layer networks of spiking neurons SM Bohte, JN Kok, H La Poutre Neurocomputing 48 (1-4), 17-37, 2002	82	2002
Visualizing a joint future of neuroscience and neuromorphic engineering F Zenke, SM Bohté, C Clopath, IM Comşa, J Göltz, W Maass, ... Neuron 109 (4), 571-575, 2021	78	2021
Spiking neural networks SM Bohte	78	2003
How attention can create synaptic tags for the learning of working memories in sequential tasks JO Rombouts, SM Bohte, PR Roelfsema PLoS computational biology 11 (3), e1004060, 2015	75	2015
The effects of pair-wise and higher-order correlations on the firing rate of a postsynaptic neuron SM Bohté, H Spekreijse, PR Roelfsema Neural Computation 12 (1), 153-179, 2000	69	2000

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