3 papers
cs.LG2026
Flat Channels to Infinity in Neural Loss Landscapes
Flavio Martinelli, Alexander Van Meegen, Berfin ÅimÅek +2
The loss landscapes of neural networks contain minima and saddle points that may be connected in flat regions or appear in isolation. We identify and characterize a special structu…
cs.AI2025
Data Augmentation Techniques to Reverse-Engineer Neural Network Weights from Input-Output Queries
Alexander Beiser, Flavio Martinelli, Wulfram Gerstner +1
Network weights can be reverse-engineered given enough informative samples of a network's input-output function. In a teacher-student setup, this translates into collecting a datas…
q-bio.NC2024
Emergent rate-based dynamics in duplicate-free populations of spiking neurons
Valentin Schmutz, Johanni Brea, Wulfram Gerstner
Can Spiking Neural Networks (SNNs) approximate the dynamics of Recurrent Neural Networks (RNNs)? Arguments in classical mean-field theory based on laws of large numbers provide a p…