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Donald Loveland
Donald Loveland
Verified email at umich.edu - Homepage
Title
Cited by
Cited by
Year
Generative counterfactual introspection for explainable deep learning
S Liu, B Kailkhura, D Loveland, Y Han
2019 IEEE global conference on signal and information processing (GlobalSIP …, 2019
1092019
Predicting compressive strength of consolidated molecular solids using computer vision and deep learning
B Gallagher, M Rever, D Loveland, TN Mundhenk, B Beauchamp, ...
Materials & Design 190, 108541, 2020
392020
The Lick AGN Monitoring Project 2016: velocity-resolved Hβ lags in luminous Seyfert galaxies
U Vivian, AJ Barth, HA Vogler, H Guo, T Treu, VN Bennert, G Canalizo, ...
The Astrophysical Journal 925 (1), 52, 2022
362022
Predicting energetics materials’ crystalline density from chemical structure by machine learning
P Nguyen, D Loveland, JT Kim, P Karande, AM Hiszpanski, TYJ Han
Journal of Chemical Information and Modeling 61 (5), 2147-2158, 2021
322021
How does heterophily impact the robustness of graph neural networks? theoretical connections and practical implications
J Zhu, J Jin, D Loveland, MT Schaub, D Koutra
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022
25*2022
Studying the [O iii]λ5007 Å emission-line width in a sample of ∼ 80 local active galaxies: a surrogate for σ?
VN Bennert, D Loveland, E Donohue, M Cosens, S Lewis, S Komossa, ...
Monthly Notices of the Royal Astronomical Society 481 (1), 138-152, 2018
212018
Fairedit: Preserving fairness in graph neural networks through greedy graph editing
D Loveland, J Pan, AF Bhathena, Y Lu
arXiv preprint arXiv:2201.03681, 2022
162022
Attribution-driven explanation of the deep neural network model via conditional microstructure image synthesis
S Liu, B Kailkhura, J Zhang, AM Hiszpanski, E Robertson, D Loveland, ...
ACS omega 7 (3), 2624-2637, 2022
7*2022
Reliable graph neural network explanations through adversarial training
D Loveland, S Liu, B Kailkhura, A Hiszpanski, Y Han
ICML 2021 Workshop on Theoretic Foundation, Criticism, and Application Trend …, 2021
72021
On graph neural network fairness in the presence of heterophilous neighborhoods
D Loveland, J Zhu, M Heimann, B Fish, MT Schaub, D Koutra
SIGKDD 2023 Deep Learning on Graphs Workshop, 2022
62022
Automated identification of molecular crystals’ packing motifs
D Loveland, B Kailkhura, P Karande, AM Hiszpanski, TYJ Han
Journal of Chemical Information and Modeling 60 (12), 6147-6154, 2020
52020
Zeroth-order sciml: Non-intrusive integration of scientific software with deep learning
I Tsaknakis, B Kailkhura, S Liu, D Loveland, J Diffenderfer, AM Hiszpanski, ...
arXiv preprint arXiv:2206.02785, 2022
32022
On Performance Discrepancies Across Local Homophily Levels in Graph Neural Networks
D Loveland, J Zhu, M Heimann, B Fish, MT Shaub, D Koutra
Learning on Graphs Conference 2023 (Spotlight), 2023
12023
Network Design through Graph Neural Networks: Identifying Challenges and Improving Performance
D Loveland, R Caceres
The 12th International Conference on Complex Networks and their Applications, 2023
2023
VizieR Online Data Catalog: LAMP 2016: velocity-resolved Hb lags in Seyfert gal.(U+, 2022)
AJ Barth, HA Vogler, H Guo, T Treu, VN Bennert, G Canalizo, ...
VizieR Online Data Catalog, J/ApJ/925/52, 2023
2023
Generative attribute optimization
S Liu, T Han, B Kailkhura, D Loveland
US Patent 11,436,427, 2022
2022
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