AI Enabled Data Quality Monitoring with Hydra. - Thomas Britton; David Lawrence; Kishansingh Rajput (CoRR, 2021)

Uncertainty aware anomaly detection to predict errant beam pulses in the SNS accelerator. - Willem Blokland; Pradeep Ramuhalli; Charles Peters; Yigit A. Yucesan; Alexander Zhukov; Malachi Schram; Kishansingh Rajput; Torri Jeske (CoRR, 2021)

Probabilistic Envelope based Visualization for Monitoring Drilling Well Data Logging. - Kishansingh Rajput; Guoning Chen (VISIGRAPP (3: IVAPP), 2022)

Time series anomaly detection in power electronics signals with recurrent and ConvLSTM autoencoders. - Majdi I. Radaideh; Chris Pappas; Jared Walden; Dan Lu 001; Lasitha Vidyaratne; Thomas Britton; Kishansingh Rajput; Malachi Schram; Sarah Cousineau (Digit. Signal Process., 2022)

Multi-module based CVAE to predict HVCM faults in the SNS accelerator. - Yasir Alanazi; Malachi Schram; Kishansingh Rajput; Steven Goldenberg; Lasitha Vidyaratne; Chris Pappas; Majdi I. Radaideh; Dan Lu 001; Pradeep Ramuhalli; Sarah Cousineau (CoRR, 2023)

Uncertainty Aware Deep Learning for Particle Accelerators. - Kishansingh Rajput; Malachi Schram; Karthik Somayaji N. S. (CoRR, 2023)

Evaluating DTW Measures via a Synthesis Framework for Time-Series Data. - Kishansingh Rajput; Duong Binh Nguyen; Guoning Chen (CoRR, 2024)

Hydra: Computer Vision for Data Quality Monitoring. - Thomas Britton; Torri Jeske; David Lawrence; Kishansingh Rajput (CoRR, 2024)

SAGIPS: A Scalable Asynchronous Generative Inverse Problem Solver. - Daniel Lersch; Malachi Schram; Zhenyu Dai; Kishansingh Rajput; Xingfu Wu; N. Sato; J. Taylor Childers (CoRR, 2024)

Distance preserving machine learning for uncertainty aware accelerator capacitance predictions. - Steven Goldenberg; Malachi Schram; Kishansingh Rajput; Thomas Britton; Chris Pappas; Dan Lu 001; Jared Walden; Majdi I. Radaideh; Sarah Cousineau; Sudarshan Harave (Mach. Learn. Sci. Technol., 2024)

Robust errant beam prognostics with conditional modeling for particle accelerators. - Kishansingh Rajput; Malachi Schram; Willem Blokland; Yasir Alanazi; Pradeep Ramuhalli; Alexander Zhukov; Charles Peters; Ricardo Vilalta (Mach. Learn. Sci. Technol., 2024)

SAGIPS: a physics-inspired scalable asynchronous generative inverse-problem solver. - Daniel Lersch; Malachi Schram; Zhenyu Dai; Kishansingh Rajput; Nobuo Sato; Xingfu Wu; J. Taylor Childers; Steven Goldenberg (Mach. Learn. Sci. Technol., 2025)

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)

Outlook Towards Deployable Continual Learning for Particle Accelerators. - Kishansingh Rajput; Sen Lin; Auralee Edelen; Willem Blokland; Malachi Schram (CoRR, 2025)

Geometric GNNs for Charged Particle Tracking at GlueX. - Ahmed Hossam Mohammed; Kishansingh Rajput; Simon Taylor; Denis Furletov; Sergey Furletov; Malachi Schram (CoRR, 2025)