3 citations · 4 across the 16 of their papers we have counts for
3 papers · 1 filter
Functional Degeneracy in Neural Networks: Measurement and Pruning
Maria Matveev, Pascal Esser, Ayush Bharadwaj +2
A central question in modern machine learning is how much a trained model can be compressed without changing its behavior, to reduce the memory, compute and energy required to depl…
Towards an Expressivity-Normalized Energy-Demand Comparison of ANNs and SNNs
Miriam Kranzlmüller, Pascal Esser, Gitta Kutyniok
Spiking neural networks (SNNs) are often regarded as energy-efficient alternatives to artificial neural networks (ANNs), yet their advantage depends critically on both network arch…
Beyond Linear and Overcomplete Regimes: A Mean-Field Analysis of Bottleneck Autoencoders
Santanu Das, Ramyak Bilas, Pascal Esser +1
Autoencoders (AEs) learn low-dimensional representations by mapping data into a latent space while minimizing reconstruction error. Despite their empirical success, theoretical und…