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)

Ultra Low Latency Machine Learning for Scientific Edge Applications. - Narasinga Rao Miniskar; Aaron R. Young; Frank Liu 001; Willem Blokland; Anthony M. Cabrera; Jeffrey S. Vetter (FPL, 2022)

Adrastea: An Efficient FPGA Design Environment for Heterogeneous Scientific Computing and Machine Learning. - Aaron R. Young; Narasinga Rao Miniskar; Frank Liu 001; Willem Blokland; Jeffrey S. Vetter (SMC, 2022)

Errant Beam Detection Using the AMD Versal ACAP and Vitis AI. - Anthony M. Cabrera; Yigit A. Yucesan; Frank Y. Liu; Willem Blokland; Jeffrey S. Vetter (HPEC, 2023)

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)

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