17 citations · 21 across the 7 of their papers we have counts for
3 papers · 1 filter
Should Under-parameterized Student Networks Copy or Average Teacher Weights?
Berfin Şimşek, Amire Bendjeddou, Wulfram Gerstner +1
Any continuous function can be approximated arbitrarily well by a neural network with sufficiently many neurons . We consider the case when itself is a neural networ…
Statistical physics, Bayesian inference and neural information processing
Erin Grant, Sandra Nestler, Berfin Şimşek +1
Lecture notes from the course given by Professor Sara A. Solla at the Les Houches summer school on "Statistical physics of Machine Learning". The notes discuss neural information p…
Expand-and-Cluster: Parameter Recovery of Neural Networks
Flavio Martinelli, Berfin Simsek, Wulfram Gerstner +1
Can we identify the weights of a neural network by probing its input-output mapping? At first glance, this problem seems to have many solutions because of permutation, overparamete…