Distributed Data and Job Management for the XENON1T Experiment. - Benedikt Riedel; Boris Bauermeister; Lincoln Bryant; Jan Conrad; Patrick de Perio; Robert W. Gardner; Luca Grandi; Francesco Lombardi; Alfio Rizzo; Gabriella Sartorelli; Marco Selvi; Evan Shockley; et al. (PEARC, 2018)

The XENON1T Data Distribution and Processing Scheme. - Daniel Ahlin; Boris Bauermeister; Jan Conrad; Robert W. Gardner; Luca Grandi; Benedikt Riedel; Evan Shockley; Judith Stephen; Ragnar Sundblad; Suchandra Thapa; Christopher D. Tunnell (CoRR, 2019)

Software Sustainability & High Energy Physics. - Daniel S. Katz; Sudhir Malik; Mark S. Neubauer; Graeme Andrew Stewart; Kétévi A. Assamagan; Erin A. Becker; Neil P. Chue Hong; Ian A. Cosden; Samuel Meehan; Edward J. W. Moyse; Adrian M. Price-Whelan; Elizabeth Sexton-Kennedy; et al. (CoRR, 2020)

Agile Scrum Development in an ad hoc Software Collaboration. - Amanda L. Baxter; Segev Y. BenZvi; Walter M. Bonivento; Adam Brazier; Michael Clark; Alexis Coleiro; David Collom; Marta Colomer-Molla; Bryce Cousins; Aliwen Delgado Orellana; Damien Dornic; Vladislav Ekimtcov; 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)

Domain-Informed Neural Networks for Interaction Localization Within Astroparticle Experiments. - Shixiao Liang; Aaron Higuera; Christina Peters; Venkat Roy; Waheed U. Bajwa; Hagit Shatkay; Christopher D. Tunnell (Frontiers Artif. Intell., 2022)

Collaborative experience between scientific software projects using Agile Scrum development. - Amanda L. Baxter; Segev Y. BenZvi; Walter M. Bonivento; Adam Brazier; Michael Clark; Alexis Coleiro; David Collom; Marta Colomer-Molla; Bryce Cousins; Aliwen Delgado Orellana; Damien Dornic; Vladislav Ekimtcov; et al. (Softw. Pract. Exp., 2022)

SOM-based Classification and a Novel Stopping Criterion for Astroparticle Applications. - Luis Sanchez; Erzsébet Merényi; Christopher D. Tunnell (ESANN, 2023)

Fast Inference Using Automatic Differentiation and Neural Transport in Astroparticle Physics. - Dorian W. P. Amaral; Shixiao Liang; Juehang Qin; Christopher D. Tunnell (CoRR, 2024)

Fast Bayesian inference for neutrino non-standard interactions at dark matter direct detection experiments. - Dorian W. P. Amaral; Shixiao Liang; Juehang Qin; Christopher D. Tunnell (Mach. Learn. Sci. Technol., 2025)

FlowVAT: Normalizing Flow Variational Inference with Affine-Invariant Tempering. - Juehang Qin; Shixiao Liang; Christopher D. Tunnell (CoRR, 2025)

Role of denoisers in simulation-based inference from graph-structured data: a case study for position inference in an astroparticle detector. - Venkat Roy; Aaron Higuera; Shixiao Liang; Christina Peters; Waheed U. Bajwa; Christopher D. Tunnell (EURASIP J. Adv. Signal Process., 2025)