Wulfram Gerstner
+41 21 693 67 13
Office:
SV 2806
EPFL › IC › IINFCOM › LCN1
Site web: https://lcn.epfl.ch/
EPFL SV BMI LCN2
AAB 1 35 (Bâtiment AAB)
Station 19
1015 Lausanne
+41 21 693 67 13
Office:
SV 2806
EPFL › SV › BMI › LCN2
Site web: https://lcn.epfl.ch/
+41 21 693 67 13
EPFL › IC › IC-SIN › SIN-ENS
Site web: https://sin.epfl.ch
+41 21 693 67 13
EPFL › SV › SV-SSV › SSV-ENS
Site web: https://sv.epfl.ch/education
+41 21 693 67 13
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Site web: https://ssc.epfl.ch
Publications représentatives
Novelty as a drive of human exploration in complex stochastic environments
A. Modirshanechi, W.-H. Lin, H.A. Xu, M. Herzog, and W. Gerstner
Published in Proc. Natl. Acad. Sci. (USA), 122:e2502193122 in 2025
High-performance deep spiking neural networks with 0.3 spikes per neuron
A. Stanojevic, S. Wozniak, G. Bellec, G. Cherubini, A. Pantazi, and W. Gerstner
Published in Nature Communications, 168: 74-88 in 2024
Local plasticity rules can learn deep representations using self-supervised contrastive predictions
B. Illing, J. Ventura, G. Bellec, and W. Gerstner
Published in 35th Conference on Neural Information Processing Systems in 2021
Diverse synaptic plasticity mechanisms orchestrated to form and retrieve memories in spiking neural networks
F. Zenke, E.J. Agnes, and W. Gerstner
Published in Nature Communications, 6:6922 in 2015
Inhibitory Plasticity Balances Excitation and Inhibition in Sensory Pathways and Memory Networks
T. Vogels, H. Sprekeler, F. Zenke, C. Clopath and W. Gerstner
Published in Science 334: 1569-1573 in 2011
Connectivity reflects coding: a model of voltage-based STDP with homeostasis
C. Clopath, L. Busing, E. Vasilaki and W. Gerstner
Published in Nature Neuroscience, 13: 344-352 in 2010
Enseignement et PhD
Doctorant·es actuel·les
Ariane Delrocq, Alisa Gross, Lucas Louis Gruaz, Flavio Martinelli, Tâm Johan Nguyen, Louis Pezon, Kasper Smeets, Shuqi Wang, Zihan Wu
A dirigé les thèses EPFL de
Angelo Arleo (2000), Laurent Badel (2008), Martin Louis Lucien Rémy Barry (2023), Brice Bathellier (2007), Sophia Becker (2026), Silvio Borer (2003), Ricardo Andres Chavarriaga Lozano (2005), Claudia Clopath (2009), Florian François Colombo (2021), Dane Sterling Corneil (2018), Mohammadjavad Faraji (2016), Nicolas Frémaux (2013), Chiara Gastaldi (2021), Felipe Gerhard (2014), Felix Gers (2001), Olivia Gozel (2019), Guillaume Hennequin (2013), Alix Herrmann Scheurer (2001), Bernd Albert Illing (2021), Renaud Jolivet (2005), Marco Philipp Lehmann (2018), Vasiliki Liakoni (2021), Nicolas Marcille (2011), Julien Mayor (2005), Skander Mensi (2014), Alireza Modirshanechi (2024), Perry Moerland (2000), Samuel Pavio Muscinelli (2018), Richard Naud (2011), Jean-Pascal Théodor Pfister (2006), Christian Antonio Pozzorini (2014), Valentin Schmutz (2022), Alex Seeholzer (2017), Hesam Setareh (2017), Denis Sheynikhovich (2007), Fabrizio Smeraldi (2000), Pierre-Edouard Sottas (2002), Mona Spiridon Paltani (2000), Ana Stanojevic (2023), Carlos Stein Naves de Brito (2016), Thomas Strösslin (2004), Christian Tomm (2012), Friedemann Zenke (2014), Lorric Ziegler (2014)
A co-dirigé les thèses EPFL de
Georgios Iatropoulos (2023), Danilo Jimenez Rezende (2013), Gediminas Luksys (2009), Laurence Meylan (2006), Berfin Simsek (2023)
Cours
Brain-style learning in neural networks
CS-479
Les réseaux de neurones artificiels sont inspirés par les réseaux de neurones biologiques, mais la version biologique ne peut pas utiliser l'algorithme backprop pour l'apprentissage. Ce cours montre le potentiel et les limites des algorithmes d'apprentissage qui sont plausible d'un point biologique.
Computational neurosciences: neuronal dynamics
NX-465
Nous étudions des modèles mathématiques de neurones et de réseaux de neurones d'un point de vue biologique et cognitive. La dynamique du cerveau est approximée par des équations differentielles et des processus stochastiques.