Actionable Attribution Maps for Scientific Machine Learning. - Shusen Liu 001; Bhavya Kailkhura; Jize Zhang; Anna M. Hiszpanski; Emily Robertson; Donald Loveland; Thomas Yong-Jin Han (CoRR, 2020)

Explainable Deep Learning for Uncovering Actionable Scientific Insights for Materials Discovery and Design. - Shusen Liu 001; Bhavya Kailkhura; Jize Zhang; Anna M. Hiszpanski; Emily Robertson; Donald Loveland; Thomas Yong-Jin Han (CoRR, 2020)

Nanomaterial Synthesis Insights from Machine Learning of Scientific Articles by Extracting, Structuring, and Visualizing Knowledge. - Anna M. Hiszpanski; Brian Gallagher; Karthik Chellappan; Peggy Li; Shusen Liu 001; Hyojin Kim 001; Jinkyu Han; Bhavya Kailkhura; David J. Buttler; Thomas Yong-Jin Han (J. Chem. Inf. Model., 2020)

Automated Identification of Molecular Crystals' Packing Motifs. - Donald Loveland; Bhavya Kailkhura; Piyush Karande; Anna M. Hiszpanski; Thomas Yong-Jin Han (J. Chem. Inf. Model., 2020)

Reliable Graph Neural Network Explanations Through Adversarial Training. - Donald Loveland; Shusen Liu 001; Bhavya Kailkhura; Anna M. Hiszpanski; Yong Han (CoRR, 2021)

Predicting Energetics Materials' Crystalline Density from Chemical Structure by Machine Learning. - Phan Nguyen; Donald Loveland; Joanne Taery Kim; Piyush Karande; Anna M. Hiszpanski; Thomas Yong-Jin Han (J. Chem. Inf. Model., 2021)

Zeroth-Order SciML: Non-intrusive Integration of Scientific Software with Deep Learning. - Ioannis C. Tsaknakis; Bhavya Kailkhura; Sijia Liu 001; Donald Loveland; James Diffenderfer; Anna Maria Hiszpanski; Mingyi Hong 001 (CoRR, 2022)

Representing Polymers as Periodic Graphs with Learned Descriptors for Accurate Polymer Property Predictions. - Evan R. Antoniuk; Peggy Li; Bhavya Kailkhura; Anna M. Hiszpanski (J. Chem. Inf. Model., 2022)

MaTableGPT: GPT-based Table Data Extractor from Materials Science Literature. - Gyeong Hoon Yi; Jiwoo Choi; Hyeongyun Song; Olivia Miano; Jaewoong Choi; Kihoon Bang; Byungju Lee; Seok Su Sohn; David Buttler; Anna M. Hiszpanski; Sang Soo Han; Donghun Kim (CoRR, 2024)

Active Learning Enables Extrapolation in Molecular Generative Models. - Evan R. Antoniuk; Peggy Li; Nathan Keilbart; Stephen Weitzner; Bhavya Kailkhura; Anna M. Hiszpanski (CoRR, 2025)

BOOM: Benchmarking Out-Of-distribution Molecular Property Predictions of Machine Learning Models. - Evan R. Antoniuk; Shehtab Zaman; Tal Ben-Nun; Peggy Li; James Diffenderfer; Busra Demirci; Obadiah Smolenski; Tim Hsu; Anna M. Hiszpanski; Kenneth Chiu; Bhavya Kailkhura; Brian Van Essen (CoRR, 2025)