Publications

Acquesta, E.C.S. (2024). Evaluating a Credibility Technical Basis Towards Trusted AI for High Consequence Applications [Conference Presentation]. 10.2172/2563820

Taylor, S.N., Neal, K.D., & Acquesta, E.C.S. (2024). Classification Using Support Vector Machines with Uncertainty Quantification [Conference Presentation]. 10.2172/2584949

Larsen, S.L., Beyeler, W.E., Acquesta, E.C.S., Klise, K.A., & Finley, P.D. (2023). Socioeconomically-inspired modeling to justify use of fine-grain mobility data. 10.2172/2463085

Larsen, S.L., Beyeler, W.E., Acquesta, E.C.S., Klise, K.A., & Finley, P.D. (2023). SES-influenced modeling to inform Strategies for Disease Control [Conference Presentation]. 10.2172/2588932

Neal, K.D., Acquesta, E.C.S., & Rushdi, A. (2023). Quantifying Data Uncertainty in Scientific Machine Learning [Conference Presentation]. 10.2172/2431202