Theses
Defense Gallery
Dissertation
Deep Learning in Neuronal and Neuromorphic Systems
Laura Kriener, PhD Thesis 2023
Learning to dream, dreaming to learn
Nicolas Deperrois, PhD Thesis 2023
Natural-gradient learning for spiking neurons
Elena Kreutzer, PhD Thesis 2021
From microscopic dynamics to ensemble behavior in spiking neural networks
Andreas Baumbach, PhD Thesis 2020
Robust learning algorithms for spiking and rate-based neural networks
Akos Kungl, PhD Thesis 2020
Harnessing function from form: towards bio-inspired artificial intelligence in neuronal substrates
Dominik Dold, PhD Thesis 2020
Solving machine learning problems with biological principles
Luziwei Leng, PhD Thesis 2019
Modeling and Verification for a Scalable Neuromorphic Substrate
Paul Müller, PhD Thesis 2017
Computing with noise in spiking neural networks
Ilja Bytschok, PhD Thesis 2017
Master
Robustness through Plasticity: A Homeostatic Mechanism for Spiking Sampling Networks
Timo Gierlich, Master's Thesis 2021
Training Deep Networks with Time-to-First-Spike Coding on the BrainScaleS Wafer-Scale System
Julian Göltz, Master's Thesis 2019
Implementing spike-based tempering on the BrainScaleS-1 mixed-signal neuromorphic system
Madison Cotteret, Master's Thesis 2019
Demonstrating Advantages of Neuromorphic Computation
Timo Wunderlich, Master's Thesis 2019
A Markovian Model of LIF Networks
Nico Gürtler, Master's Thesis 2018
Spatio-Temporal Predictions with Spiking Neural Networks
Maximilian Zenk, Master's Thesis 2018
Simulated Tempering in Spiking Neural Networks
Agnes Korcsak-Gorzo, Master's Thesis 2017
Sampling with leaky integrate-and-fire neurons on the HICANNv4 neuromorphic chip
Akos Kungl, Master's Thesis 2016
Magnetic Phenomena in Spiking Neural Networks
Andreas Baumbach, Master's Thesis 2016
Stochastic Computation in Spiking Neural Networks Without Noise
Dominik Dold, Master's Thesis 2016
Towards a Neuromorphic Implementation of Spike-Based Expectation Maximization
Oliver Breitwieser, Master's Thesis 2015
Generative Properties of LIF-based Boltzmann Machines
Roman Martel, Master's Thesis 2015
A Neural Implementation of Probabilistic Inference in Binary Probability Spaces
Dimitri Probst, Master's Thesis 2014
Deep Learning Architectures for Neuromorphic Hardware
Luziwei Leng, Master's Thesis 2014
Bachelor
The Effect of Asymmetric Weight Variability on Sampling Processes based on Boltzmann Machines in Neuromorphic Hardware Applications
Jannik Fehre, Bachelor's Thesis 2017
Accelerated Classification in Hierarchical Neural Networks on Neuromorphic Hardware
Carola Fischer, Bachelor's Thesis 2017
Struktur schafft Robustheit: Eine Untersuchung hierarchischer neuronaler Netzwerke mit unpräzisen Komponenten
Anna Schroeder, Bachelor's Thesis 2016
STDP-Based Contrastive Divergence Training for LIF-Based Boltzmann Machines
Christian Weilbach, Bachelor's Thesis 2015
Firing States of Recurrent Leaky Integrate-and-Fire Networks
Agnes Korcsak-Gorzo, Bachelor's Thesis 2015
Boltzmann Sampling with Neuromorphic Hardware
David Stöckel, Bachelor's Thesis 2015
Predictive Stochastic Inference: From Abstract Models to Neuromorphic Implementation
Marco Roth, Bachelor's Thesis 2015
On the Memory Characteristic of a Cortical Attractor Network
Boris Rivkin, Bachelor's Thesis 2014
Distanzmaße für Spiketrains im Rahmen der Optimierung von Neuronparametern
Jonathan Born, Bachelor's Thesis 2012
Investigation of a Cortical Attractor-Memory Network
Oliver Breitwieser, Bachelor's Thesis 2011
Diploma
Toward Belief Propagation on Neuromorphic Hardware
Venelin Petkov, Diploma Thesis 2012
From Shared Input to correlated Neuron Dynamics: Development of a Predictive Framework
Ilja Bytschok, Diploma Thesis 2011
Distortions of Neural Network Models Induced by Their Emulation on Neuromorphic Hardware Devices
Paul Müller, Diploma Thesis 2011