Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Dejan Pecevski

Showing results (1-10 of 9) with videos related to

Pageof 1
Sort By:
Eneuro|July 16, 2016
Learning Probabilistic Inference through Spike-Timing-Dependent PlasticityDejan Pecevski, Wolfgang Maass
Plos Computational Biology|October 11, 2008
A learning theory for reward-modulated spike-timing-dependent plasticity with application to biofeedbackRobert Legenstein, Dejan Pecevski, Wolfgang Maass
Frontiers in Neuroinformatics|June 23, 2009
[Not Available]Dejan Pecevski, Thomas Natschläger, Klaus Schuch
Plos Computational Biology|January 6, 2012
Probabilistic inference in general graphical models through sampling in stochastic networks of spiking neuronsDejan Pecevski, Lars Buesing, Wolfgang Maass
Frontiers in Neuroinformatics|September 2, 2014
NEVESIM: event-driven neural simulation framework with a Python interfaceDejan Pecevski, David Kappel, Zeno Jonke
Scientific Reports|February 19, 2016
Recurrent Spiking Networks Solve Planning TasksElmar Rueckert, David Kappel, Daniel Tanneberg, et al.
Frontiers in Computational Neuroscience|March 3, 2015
Probabilistic inference in discrete spaces can be implemented into networks of LIF neuronsDimitri Probst, Mihai A Petrovici, Ilja Bytschok, et al.
Frontiers in Neuroinformatics|February 6, 2009
PyNN: A Common Interface for Neuronal Network SimulatorsAndrew P Davison, Daniel Brüderle, Jochen Eppler, et al.
Journal of Computational Neuroscience|July 17, 2007
Simulation of networks of spiking neurons: a review of tools and strategiesRomain Brette, Michelle Rudolph, Ted Carnevale, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
Eneuro|July 16, 2016
Learning Probabilistic Inference through Spike-Timing-Dependent PlasticityDejan Pecevski, Wolfgang Maass
Plos Computational Biology|October 11, 2008
A learning theory for reward-modulated spike-timing-dependent plasticity with application to biofeedbackRobert Legenstein, Dejan Pecevski, Wolfgang Maass
Frontiers in Neuroinformatics|June 23, 2009
[Not Available]Dejan Pecevski, Thomas Natschläger, Klaus Schuch
Plos Computational Biology|January 6, 2012
Probabilistic inference in general graphical models through sampling in stochastic networks of spiking neuronsDejan Pecevski, Lars Buesing, Wolfgang Maass
Frontiers in Neuroinformatics|September 2, 2014
NEVESIM: event-driven neural simulation framework with a Python interfaceDejan Pecevski, David Kappel, Zeno Jonke
Scientific Reports|February 19, 2016
Recurrent Spiking Networks Solve Planning TasksElmar Rueckert, David Kappel, Daniel Tanneberg, et al.
Frontiers in Computational Neuroscience|March 3, 2015
Probabilistic inference in discrete spaces can be implemented into networks of LIF neuronsDimitri Probst, Mihai A Petrovici, Ilja Bytschok, et al.
Frontiers in Neuroinformatics|February 6, 2009
PyNN: A Common Interface for Neuronal Network SimulatorsAndrew P Davison, Daniel Brüderle, Jochen Eppler, et al.
Journal of Computational Neuroscience|July 17, 2007
Simulation of networks of spiking neurons: a review of tools and strategiesRomain Brette, Michelle Rudolph, Ted Carnevale, et al.
Pageof 1