Donald Loveland

Publication Activity (10 Years)

Years Active: 2019-2023
Publications (10 Years): 15

Top Topics

Heuristic Solution

Top Venues

J. Chem. Inf. Model.

Publications

Donald Loveland, Jiong Zhu, Mark Heimann, Benjamin Fish, Michael T. Schaub, Danai Koutra
On Performance Discrepancies Across Local Homophily Levels in Graph Neural Networks. CoRR (2023)
Donald Loveland, Rajmonda Caceres
Network Design Through Graph Neural Networks: Identifying Challenges and Improving Performance. COMPLEX NETWORKS (1) (2023)
Donald Loveland, Rajmonda Caceres
Network Design through Graph Neural Networks: Identifying Challenges and Improving Performance. CoRR (2023)
Donald Loveland, Jiong Zhu, Mark Heimann, Benjamin Fish, Michael T. Schaub, Danai Koutra
On Performance Discrepancies Across Local Homophily Levels in Graph Neural Networks. LoG (2023)
Donald Loveland, Jiong Zhu, Mark Heimann, Ben Fish, Michael T. Schaub, Danai Koutra
On Graph Neural Network Fairness in the Presence of Heterophilous Neighborhoods. CoRR (2022)
Ioannis C. Tsaknakis, Bhavya Kailkhura, Sijia Liu, Donald Loveland, James Diffenderfer, Anna Maria Hiszpanski, Mingyi Hong
Zeroth-Order SciML: Non-intrusive Integration of Scientific Software with Deep Learning. CoRR (2022)
Jiong Zhu, Junchen Jin, Donald Loveland, Michael T. Schaub, Danai Koutra
How does Heterophily Impact the Robustness of Graph Neural Networks?: Theoretical Connections and Practical Implications. KDD (2022)
Donald Loveland, Jiayi Pan, Aaresh Farrokh Bhathena, Yiyang Lu
FairEdit: Preserving Fairness in Graph Neural Networks through Greedy Graph Editing. CoRR (2022)
Phan Nguyen, Donald Loveland, Joanne T. Kim, Piyush Karande, Anna M. Hiszpanski, Thomas Yong-Jin Han
Predicting Energetics Materials' Crystalline Density from Chemical Structure by Machine Learning. J. Chem. Inf. Model. 61 (5) (2021)
Donald Loveland, Shusen Liu, Bhavya Kailkhura, Anna M. Hiszpanski, Yong Han
Reliable Graph Neural Network Explanations Through Adversarial Training. CoRR (2021)
Shusen Liu, Bhavya Kailkhura, Jize Zhang, Anna M. Hiszpanski, Emily Robertson, Donald Loveland, Thomas Yong-Jin Han
Explainable Deep Learning for Uncovering Actionable Scientific Insights for Materials Discovery and Design. CoRR (2020)
Donald Loveland, Bhavya Kailkhura, Piyush Karande, Anna M. Hiszpanski, Thomas Yong-Jin Han
Automated Identification of Molecular Crystals' Packing Motifs. J. Chem. Inf. Model. 60 (12) (2020)
Shusen Liu, Bhavya Kailkhura, Jize Zhang, Anna M. Hiszpanski, Emily Robertson, Donald Loveland, Thomas Yong-Jin Han
Actionable Attribution Maps for Scientific Machine Learning. CoRR (2020)
Shusen Liu, Bhavya Kailkhura, Donald Loveland, Yong Han
Generative Counterfactual Introspection for Explainable Deep Learning. GlobalSIP (2019)
Shusen Liu, Bhavya Kailkhura, Donald Loveland, Yong Han
Generative Counterfactual Introspection for Explainable Deep Learning. CoRR (2019)