Neutrino-KAVE: An immersive visualization and fitting tool for neutrino physics education. - Elizabeth Izatt; Kate Scholberg; Regis Kopper (VR, 2014)

Applications and Techniques for Fast Machine Learning in Science. - Allison McCarn Deiana; Nhan Tran; Joshua Agar; Michaela Blott; Giuseppe Di Guglielmo; Javier M. Duarte; Philip C. Harris; Scott Hauck; Mia Liu; Mark S. Neubauer; Jennifer Ngadiuba; Seda Ogrenci Memik; et al. (CoRR, 2021)

SNEWPY: A Data Pipeline from Supernova Simulations to Neutrino Signals. - Amanda L. Baxter; Segev Y. BenZvi; Joahan Jaimes; Alexis Coleiro; Marta Molla; Damien Dornic; Spencer Griswold; Tomer Goldhagen; Anne Graf; Alec Habig; Remington Hill; Shunsaku Horiuchi; et al. (J. Open Source Softw., 2021)

Applications and Techniques for Fast Machine Learning in Science. - Allison McCarn Deiana; Nhan Tran; Joshua Agar; Michaela Blott; Giuseppe Di Guglielmo; Javier M. Duarte; Philip C. Harris; Scott Hauck; Mia Liu; Mark S. Neubauer; Jennifer Ngadiuba; Seda Ogrenci Memik; et al. (Frontiers Big Data, 2022)

Corrigendum: Applications and techniques for fast machine learning in science. - Allison McCarn Deiana; Nhan Tran; Joshua Agar; Michaela Blott; Giuseppe Di Guglielmo; Javier M. Duarte; Philip C. Harris; Scott Hauck; Mia Liu; Mark S. Neubauer; Jennifer Ngadiuba; Seda Ogrenci-Memik; et al. (Frontiers Big Data, 2024)