Publications |

Multi-Time Scale State Estimation of Vehicle Dynamics Using Physics-Informed Neural Process

Tue, 28 Apr 2026 00:00:00 +0000

Hunter, D., Augsburger, J., & O’Rourke, S. (2026). Multi-time scale state estimation of vehicle dynamics using physics-informed neural process. SPIE Defense + Security 2026.

Accepted at SPIE Defense + Security 2026.

Fri, 27 Mar 2026 00:00:00 +0000

Hunter, D., & Enyioha, C. (2026). Real-time performance analysis of multi-fidelity residual physics-informed neural process-based state estimation for robotic systems. International Conference on Robotics, Control and Automation (ICRCA).

Accepted at ICRCA 2026.

Thu, 05 Mar 2026 00:00:00 +0000

Hunter, D., & Enyioha, C. (2026). Neural process-based reactive controller for autonomous racing. IEEE SoutheastCon 2026.

Accepted at IEEE SoutheastCon 2026.

Mon, 01 Sep 2025 00:00:00 +0000

Hunter, D., & Enyioha, C. (2025). Hybrid state estimation of uncertain nonlinear dynamics using neural processes. Springer Nature Machine Learning Journal (under review).

Preprint available at:

Fri, 01 May 2020 00:00:00 +0000

Hunter, D., & Bowers, C. (2020). Quantifying the difference of time complexity between two probability algorithms. Edward Waters College’s Undergraduate Journal on Research Across the Disciplines, 1(2), 76–97.