Dejan Pecevski

According to our database, Dejan Pecevski authored at least 9 papers between 2007 and 2015.

Collaborative distances:

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

2015

Probabilistic inference in discrete spaces can be implemented into networks of LIF neurons.

Dimitri Probst, Mihai A. Petrovici, Ilja Bytschok, Johannes Bill, Dejan Pecevski, Johannes Schemmel, Karlheinz Meier

Frontiers Comput. Neurosci., 2015

2014

NEVESIM: event-driven neural simulation framework with a Python interface.

Dejan Pecevski, David Kappel, Zeno Jonke

Frontiers Neuroinformatics, 2014

2012

Oger: modular learning architectures for large-scale sequential processing.

David Verstraeten, Benjamin Schrauwen, Sander Dieleman, Philemon Brakel, Pieter Buteneers, Dejan Pecevski

J. Mach. Learn. Res., 2012

2011

Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons.

Dejan Pecevski, Lars Buesing, Wolfgang Maass

PLoS Comput. Biol., 2011

2009

PCSIM: a parallel simulation environment for neural circuits fully integrated with Python.

Dejan Pecevski, Thomas Natschläger, Klaus Schuch

Frontiers Neuroinformatics, 2009

2008

A Learning Theory for Reward-Modulated Spike-Timing-Dependent Plasticity with Application to Biofeedback.

Robert Legenstein, Dejan Pecevski, Wolfgang Maass

PLoS Comput. Biol., 2008

PyNN: a common interface for neuronal network simulators.

Andrew P. Davison, Daniel Brüderle, Jochen M. Eppler, Jens Kremkow, Eilif B. Müller, Dejan Pecevski, Laurent U. Perrinet, Pierre Yger

Frontiers Neuroinformatics, 2008

2007

Simulation of networks of spiking neurons: A review of tools and strategies.

Romain Brette, Michelle Rudolph, Ted Carnevale, Michael L. Hines, David Beeman, James M. Bower, Markus Diesmann, Abigail Morrison, Philip H. Goodman, Frederick C. Harris Jr., Milind Zirpe, Thomas Natschläger, Dejan Pecevski, Bard Ermentrout, Mikael Djurfeldt, Anders Lansner, Olivier Rochel, Thierry Viéville, Eilif B. Muller, Andrew P. Davison, Sami El Boustani, Alain Destexhe

J. Comput. Neurosci., 2007

Theoretical Analysis of Learning with Reward-Modulated Spike-Timing-Dependent Plasticity.

Robert Legenstein, Dejan Pecevski, Wolfgang Maass

Proceedings of the Advances in Neural Information Processing Systems 20, 2007