Jie Bu — accepted AI-conference papers

2023

Mitigating Propagation Failures in Physics-informed Neural Networks using Retain-Resample-Release (R3) Sampling

Arka Daw, Jie Bu, Sifan Wang, Paris Perdikaris, Anuj Karpatne

ICML 2023poster

Despite the success of physics-informed neural networks (PINNs) in approximating partial differential equations (PDEs), PINNs can sometimes fail to converge to the correct solution in problems involving complicated PDEs. This is reflected in several recent studies on characterizing the "failure mode…

Cited by 69 Source ↗PDF ↗code ↗Scholar ↗

2021

Learning Compact Representations of Neural Networks using DiscriminAtive Masking (DAM)

Jie Bu, Arka Daw, M. Maruf, Anuj Karpatne

NeurIPS 2021poster

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 and structured network pruning. While there is a growing body of work in structured pruning, current state-of-the-art me…

Cited by 8 Source ↗PDF ↗code ↗Scholar ↗