This repository contains the source code and videos for the paper: A spring–block theory of feature learning in deep neural networks. More details can be found here.
When slow and steady pulling:
ruler_lazy.mp4
and the corresponding lazy training of a non-linear DNN:
dnn_lazy.mp4
When quick and jerky pulling:
ruler_active.mp4
and the corresponding active training of a non-linear DNN:
dnn_active.mp4
./bash/test_pd_ns_nl.sh # data noise
./bash/test_pd_lr_nl.sh # learning rate
./bash/test_pd_dp_nl.sh # drop out
./bash/test_pd_bm_nl.sh # batch size
In the first notebook, we solve the first-order overdamping system by discrete iteration.
In the second notebook, we solve the second-order stochastic differential equation using sdeint.