3 citations · 4 across the 3 of their papers we have counts for
4 papers
Reflecting brownian motion and the gauss-bonnet-chern theorem
Weitao Du, Elton P. Hsu
We use reflecting Brownian motion (RBM) to prove the well known Gauss-Bonnet-Chern theorem for a compact Riemannian manifold with boundary. The boundary integrand is obtained by ca…
Implicit bias of deep linear networks in the large learning rate phase
Wei Huang, Weitao Du, Richard Yi Da Xu +1
Most theoretical studies explaining the regularization effect in deep learning have only focused on gradient descent with a sufficient small learning rate or even gradient flow (in…
Constructing exchangeable pairs by diffusion on manifolds and its application
Weitao Du
We construct a continuous family of exchangeable pairs by perturbing the random variable through diffusion processes on manifold in order to apply Stein method to certain geometric…
Mean field theory for deep dropout networks: digging up gradient backpropagation deeply
Wei Huang, Richard Yi Da Xu, Weitao Du +2
In recent years, the mean field theory has been applied to the study of neural networks and has achieved a great deal of success. The theory has been applied to various neural netw…