23 citations · 24 across the 7 of their papers we have counts for
7 papers
LatentFlow: Visual Analytics for Latent Space Analysis in Molecular Graph Neural Networks
Shiyi Liu, Jiaqing Chen, Nicholas Hadler +6
Chemists and materials scientists increasingly use machine learning models, such as graph neural networks (GNNs), to predict properties of molecules and the outcomes of their react…
Characterizing Atomistic Transitions Using Cross-scale Graph-pooled Chebyshev Signatures
Rostyslav Hnatyshyn, Danny Perez
Large-scale atomistic simulations can produce extreme volumes of information in the form of long trajectories. Reliably and automatically extracting key information from such datas…
Landscaper: Understanding Loss Landscapes Through Multi-Dimensional Topological Analysis
Jiaqing Chen, Nicholas Hadler, Tiankai Xie +8
Loss landscapes are a powerful tool for understanding neural network optimization and generalization, yet traditional low-dimensional analyses often miss complex topological featur…
LAMDA: Aiding Visual Exploration of Atomic Displacements in Molecular Dynamics Simulations
Rostyslav Hnatyshyn, Danny Perez, Gerik Scheuermann +2
Contemporary materials science research is heavily conducted in silico, involving massive simulations of the atomic-scale evolution of materials. Cataloging basic patterns in the a…
Capturing Cancer as Music: Cancer Mechanisms Expressed through Musification
Rostyslav Hnatyshyn, Jiayi Hong, Ross Maciejewski +2
The development of cancer is difficult to express on a simple and intuitive level due to its complexity. Since cancer is so widespread, raising public awareness about its mechanism…
A Survey of Designs for Combined 2D+3D Visual Representations
Jiayi Hong, Rostyslav Hnatyshyn, Ebrar A. D. Santos +2
We examine visual representations of data that make use of combinations of both 2D and 3D data mappings. Combining 2D and 3D representations is a common technique that allows viewe…