Felix Weissenberger

I did my PhD under the supervision of Angelika Steger with a focus on the role of randomness as a principle of structure and computation in neural networks. I am interested in using insights from neuroscience for machine learning and how problems at the frontiers of machine learning can guide our research in neuroscience.

Publications and Preprints

A hippocampal model for behavioral time acquisition and fast bidirectional replay of spatio-temporal memory sequences
video abstract
joint work with H. Einarsson, M. Gauy, J. Lengler, F. Meier, M. Yanik and A. Steger
preprint on bioRxiv, 2018

On the origin of lognormal network synchrony in CA1
joint work with H. Einarsson, M. Gauy, F. Meier, A. Mujika, J. Lengler and A. Steger
Hippocampus, 2018

The linear hidden subset problem for the (1+1) EA with scheduled and adaptive mutation rates
joint work with H. Einarsson, M. Gauy, F. Meier, A. Mujika, J. Lengler and A. Steger
GECCO, 2018

Voltage dependence of synaptic plasticity is essential for rate based learning with short stimuli
joint work with M. Gauy, J. Lengler, F. Meier and A. Steger
Nature Scientific Reports, 2018

Long synfire chains emerge by spike-timing dependent plasticity modulated by population activity
joint work with F. Meier, J. Lengler, H. Einarsson and A. Steger
International Journal of Neural Systems, 2017

A tight Erdős-Pósa function for long cycles
joint work with F. Mousset, A. Noever and N. Škorić
Journal of Combinatorial Theory, Series B, 2017