Online tuning and light source control using a physics-informed Gaussian process Adi. - Adi Hanuka; Joseph Duris; Jane Shtalenkova; Dylan Kennedy; Auralee Edelen; Daniel Ratner; Xiaobiao Huang (CoRR, 2019)

Physics-informed Gaussian Process for Online Optimization of Particle Accelerators. - Adi Hanuka; Xiaobiao Huang; Jane Shtalenkova; Dylan Kennedy; Auralee Edelen; V. R. Lalchand; Daniel Ratner; Joseph Duris (CoRR, 2020)

Accurate and confident prediction of electron beam longitudinal properties using spectral virtual diagnostics. - Adi Hanuka; Claudio Emma; Timothy Maxwell; Alanb S. Fisher; Bryce Jacobson; Marc J. Hogan; Zhirong Huang (CoRR, 2020)

Accurate Machine Learning-based Diagnostic with Quantified Uncertainties. - Adi Hanuka; Owen Convery (AAAI Spring Symposium: MLPS, 2021)

Quantifying Uncertainty for Machine Learning Based Diagnostic. - Owen Convery; Lewis Smith; Yarin Gal; Adi Hanuka (CoRR, 2021)

Simulation Intelligence: Towards a New Generation of Scientific Methods. - Alexander Lavin; Hector Zenil; Brooks Paige; David Krakauer; Justin Gottschlich; Tim Mattson; Anima Anandkumar; Sanjay Choudry; Kamil Rocki; Atilim Günes Baydin; Carina Prunkl; Olexandr Isayev; et al. (CoRR, 2021)

Virtual Diagnostic Suite for Electron Beam Prediction and Control at FACET-II. - Claudio Emma; Auralee Edelen; Adi Hanuka; Brendan O'Shea; Alexander Scheinker (Inf., 2021)