In this work, we reveal a strong implicit bias of stochastic gradient de...
In this work, we explore the maximum-margin bias of quasi-homogeneous ne...
In this work we explore the limiting dynamics of deep neural networks tr...
In nature, symmetry governs regularities, while symmetry breaking brings...
Predicting the dynamics of neural network parameters during training is ...
Pruning the parameters of deep neural networks has generated intense int...
The neural plausibility of backpropagation has long been disputed, prima...
Autoencoders are a deep learning model for representation learning. When...