17 citations · 22 across the 4 of their papers we have counts for
4 papers
Learning Compact Representations of Neural Networks using DiscriminAtive Masking (DAM)
Jie Bu, Arka Daw, M. Maruf +1
A central goal in deep learning is to learn compact representations of features at every layer of a neural network, which is useful for both unsupervised representation learning an…
Quadratic Residual Networks: A New Class of Neural Networks for Solving Forward and Inverse Problems in Physics Involving PDEs
Jie Bu, Anuj Karpatne
We propose quadratic residual networks (QRes) as a new type of parameter-efficient neural network architecture, by adding a quadratic residual term to the weighted sum of inputs be…
Beyond Observed Connections : Link Injection
Jie Bu, M. Maruf, Arka Daw
In this paper, we proposed the \textit{link injection}, a novel method that helps any differentiable graph machine learning models to go beyond observed connections from the input…
Physics-guided Design and Learning of Neural Networks for Predicting Drag Force on Particle Suspensions in Moving Fluids
Nikhil Muralidhar, Jie Bu, Ze Cao +4
Physics-based simulations are often used to model and understand complex physical systems and processes in domains like fluid dynamics. Such simulations, although used frequently,…