Creating Audio Based Experiments as Social Web Games with the CASimIR Framework. - Daniel Wolff; Guillaume Bellec; Anders Friberg; Andrew MacFarlane 001; Tillman Weyde (Semantic Audio, 2014)

Slow feature analysis with spiking neurons and its application to audio stimuli. - Guillaume Bellec; Mathieu Galtier; Romain Brette; Pierre Yger (J. Comput. Neurosci., 2016)

Neuromorphic hardware in the loop: Training a deep spiking network on the BrainScaleS wafer-scale system. - Sebastian Schmitt; Johann Klähn; Guillaume Bellec; Andreas Grübl; Maurice Güttler; Andreas Hartel; Stephan Hartmann 002; Dan Husmann de Oliveira; Kai Husmann; Sebastian Jeltsch; Vitali Karasenko; Mitja Kleider; et al. (IJCNN, 2017)

Pattern representation and recognition with accelerated analog neuromorphic systems. - Mihai A. Petrovici; Sebastian Schmitt; Johann Klähn; Robert D. St. Louis; Anna Schroeder; Guillaume Bellec; Johannes Bill; Oliver Breitwieser; Ilja Bytschok; Andreas Grübl; Maurice Güttler; Andreas Hartel; et al. (ISCAS, 2017)

Pattern representation and recognition with accelerated analog neuromorphic systems. - Mihai A. Petrovici; Sebastian Schmitt; Johann Klähn; David Stöckel; Anna Schroeder; Guillaume Bellec; Johannes Bill; Oliver Breitwieser; Ilja Bytschok; Andreas Grübl; Maurice Güttler; Andreas Hartel; et al. (CoRR, 2017)

Neuromorphic Hardware In The Loop: Training a Deep Spiking Network on the BrainScaleS Wafer-Scale System. - Sebastian Schmitt; Johann Klaehn; Guillaume Bellec; Andreas Grübl; Maurice Guettler; Andreas Hartel; Stephan Hartmann 002; Dan Husmann de Oliveira; Kai Husmann; Vitali Karasenko; Mitja Kleider; Christoph Koke; et al. (CoRR, 2017)

Deep Rewiring: Training very sparse deep networks. - Guillaume Bellec; David Kappel; Wolfgang Maass 001; Robert Legenstein (ICLR (Poster), 2018)

Long short-term memory and Learning-to-learn in networks of spiking neurons. - Guillaume Bellec; Darjan Salaj; Anand Subramoney; Robert Legenstein; Wolfgang Maass 001 (NeurIPS, 2018)

Biologically inspired alternatives to backpropagation through time for learning in recurrent neural nets. - Guillaume Bellec; Franz Scherr; Elias Hajek; Darjan Salaj; Robert Legenstein; Wolfgang Maass 001 (CoRR, 2019)

Towards truly local gradients with CLAPP: Contrastive, Local And Predictive Plasticity. - Bernd Illing; Wulfram Gerstner; Guillaume Bellec (CoRR, 2020)

Fitting summary statistics of neural data with a differentiable spiking network simulator. - Guillaume Bellec; Shuqi Wang; Alireza Modirshanechi; Johanni Brea; Wulfram Gerstner (NeurIPS, 2021)

Local plasticity rules can learn deep representations using self-supervised contrastive predictions. - Bernd Illing; Jean Ventura; Guillaume Bellec; Wulfram Gerstner (NeurIPS, 2021)

Mesoscopic modeling of hidden spiking neurons. - Shuqi Wang; Valentin Schmutz; Guillaume Bellec; Wulfram Gerstner (NeurIPS, 2022)

Trial matching: capturing variability with data-constrained spiking neural networks. - Christos Sourmpis; Carl C. H. Petersen; Wulfram Gerstner; Guillaume Bellec (NeurIPS, 2023)

GateON: an unsupervised method for large scale continual learning. - Martin Barry; Guillaume Bellec; Wulfram Gerstner (CoRR, 2023)

Are training trajectories of deep single-spike and deep ReLU network equivalent? - Ana Stanojevic; Stanislaw Wozniak; Guillaume Bellec; Giovanni Cherubini; Angeliki Pantazi; Wulfram Gerstner (CoRR, 2023)

An exact mapping from ReLU networks to spiking neural networks. - Ana Stanojevic; Stanislaw Wozniak; Guillaume Bellec; Giovanni Cherubini; Angeliki Pantazi; Wulfram Gerstner (Neural Networks, 2023)

Spiking Music: Audio Compression with Event Based Auto-encoders. - Martim Lisboa; Guillaume Bellec (CoRR, 2024)

Corrigendum to 'An exact mapping from ReLU networks to spiking neural networks' [Neural Networks Volume 168 (2023) Pages 74-88]. - Ana Stanojevic; Stanislaw Wozniak; Guillaume Bellec; Giovanni Cherubini; Angeliki Pantazi; Wulfram Gerstner (Neural Networks, 2024)