15 citations · 21 across the 4 of their papers we have counts for
4 papers
Proximal Implicit ODE Solvers for Accelerating Learning Neural ODEs
Justin Baker, Hedi Xia, Yiwei Wang +7
Learning neural ODEs often requires solving very stiff ODE systems, primarily using explicit adaptive step size ODE solvers. These solvers are computationally expensive, requiring…
How Does Momentum Benefit Deep Neural Networks Architecture Design? A Few Case Studies
Bao Wang, Hedi Xia, Tan Nguyen +1
We present and review an algorithmic and theoretical framework for improving neural network architecture design via momentum. As case studies, we consider how momentum can improve…
Heavy Ball Neural Ordinary Differential Equations
Hedi Xia, Vai Suliafu, Hangjie Ji +4
We propose heavy ball neural ordinary differential equations (HBNODEs), leveraging the continuous limit of the classical momentum accelerated gradient descent, to improve neural OD…
Kernel Treelets
Hedi Xia, Hector D. Ceniceros
A new method for hierarchical clustering is presented. It combines treelets, a particular multiscale decomposition of data, with a projection on a reproducing kernel Hilbert space.…