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Fitting summary statistics of neural data with a differentiable spiking network simulator

Jun 18, 2021
Guillaume Bellec, Shuqi Wang, Alireza Modirshanechi, Johanni Brea, Wulfram Gerstner

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Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances

May 25, 2021
Berfin Şimşek, François Ged, Arthur Jacot, Francesco Spadaro, Clément Hongler, Wulfram Gerstner, Johanni Brea

* To appear at ICML 2021 

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An Approximate Bayesian Approach to Surprise-Based Learning

Jul 05, 2019
Vasiliki Liakoni, Alireza Modirshanechi, Wulfram Gerstner, Johanni Brea

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Weight-space symmetry in deep networks gives rise to permutation saddles, connected by equal-loss valleys across the loss landscape

Jul 05, 2019
Johanni Brea, Berfin Simsek, Bernd Illing, Wulfram Gerstner

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GaussianProcesses.jl: A Nonparametric Bayes package for the Julia Language

Dec 21, 2018
Jamie Fairbrother, Christopher Nemeth, Maxime Rischard, Johanni Brea

* 23 pages, 8 figures 

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Learning to Generate Music with BachProp

Dec 17, 2018
Florian Colombo, Johanni Brea, Wulfram Gerstner

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Is prioritized sweeping the better episodic control?

Aug 09, 2018
Johanni Brea

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Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation

Jun 11, 2018
Dane Corneil, Wulfram Gerstner, Johanni Brea

* Accepted at ICML 2018; camera-ready version 

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Towards deep learning with spiking neurons in energy based models with contrastive Hebbian plasticity

Dec 09, 2016
Thomas Mesnard, Wulfram Gerstner, Johanni Brea

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Algorithmic Composition of Melodies with Deep Recurrent Neural Networks

Jun 23, 2016
Florian Colombo, Samuel P. Muscinelli, Alexander Seeholzer, Johanni Brea, Wulfram Gerstner

* Proceeding of the 1st Conference on Computer Simulation of Musical Creativity, Huddersfield University 

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