37 citations · 39 across the 3 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…
PID-GAN: A GAN Framework based on a Physics-informed Discriminator for Uncertainty Quantification with Physics
Arka Daw, M. Maruf, Anuj Karpatne
As applications of deep learning (DL) continue to seep into critical scientific use-cases, the importance of performing uncertainty quantification (UQ) with DL has become more pres…
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…
Maximizing Cohesion and Separation in Graph Representation Learning: A Distance-aware Negative Sampling Approach
M. Maruf, Anuj Karpatne
The objective of unsupervised graph representation learning (GRL) is to learn a low-dimensional space of node embeddings that reflect the structure of a given unlabeled graph. Exis…