Superconducting radio-frequency cavity fault classification using machine learning at Jefferson Laboratory. - Chris Tennant; Adam Carpenter; Tom Powers; Anna Shabalina Solopova; Lasitha Vidyaratne; Khan Iftekharuddin (CoRR, 2020)

Deep Learning Based Superconducting Radio-Frequency Cavity Fault Classification at Jefferson Laboratory. - Lasitha Vidyaratne; Adam Carpenter; Tom Powers; Chris Tennant; Khan M. Iftekharuddin; Md Monibor Rahman; Anna Shabalina Solopova (Frontiers Artif. Intell., 2021)

Uncertainty Aware Deep Learning for Fault Prediction Using Multivariate Time Series Signals. - Md Monibor Rahman; Lasitha Vidyaratne; Adam Carpenter; Chris Tennant; Khan M. Iftekharuddin (IJCNN, 2023)

Anomaly Detection of Particle Orbit in Accelerator using LSTM Deep Learning Technology. - Zhiyuan Chen 003; Wei Lu; Radhika Bhong; Yimin Hu; Brian Freeman; Adam Carpenter (CoRR, 2024)

Data-Driven Gradient Optimization for Field Emission Management in a Superconducting Radio-Frequency Linac. - Steven Goldenberg; Kawser Ahammed; Adam Carpenter; Jiang Li; Riad Suleiman; Chris Tennant (CoRR, 2024)

Accelerating cavity fault prediction using deep learning at Jefferson Laboratory. - Md Monibor Rahman; Adam Carpenter; Khan M. Iftekharuddin; Chris Tennant (Mach. Learn. Sci. Technol., 2024)

Harnessing the power of gradient-based simulations for multi-objective optimization in particle accelerators. - Kishansingh Rajput; Malachi Schram; Auralee Edelen; Jonathan Colen; Armen Kasparian; Ryan Roussel; Adam Carpenter; He Zhang; Jay Benesch (Mach. Learn. Sci. Technol., 2025)

eLog analysis for accelerators: status and future outlook. - Antonin Sulc; Thorsten Hellert; Aaron Reed; Adam Carpenter; Alex Bien; Chris Tennant; Claudio Bisegni; Daniel Lersch; Daniel Ratner; David Lawrence; Diana McSpadden; Hayden Hoschouer; et al. (CoRR, 2025)