Generative Machine Learning for Robust Free-Space Communication. - Sanjaya Lohani; Ryan T. Glasser (CoRR, 2019)

Dispersion Characterization and Pulse Prediction with Machine Learning. - Sanjaya Lohani; Erin M. Knutson; Wenlei Zhang; Ryan T. Glasser (CoRR, 2019)

On the experimental feasibility of quantum state reconstruction via machine learning. - Sanjaya Lohani; Thomas A. Searles; Brian T. Kirby; Ryan T. Glasser (CoRR, 2020)

Coherent optical communications enhanced by machine intelligence. - Sanjaya Lohani; Ryan T. Glasser (Mach. Learn. Sci. Technol., 2020)

Machine learning assisted quantum state estimation. - Sanjaya Lohani; Brian T. Kirby; Michael Brodsky; Onur Danaci; Ryan T. Glasser (Mach. Learn. Sci. Technol., 2020)

Improving application performance with biased distributions of quantum states. - Sanjaya Lohani; Joseph M. Lukens; Daniel E. Jones; Thomas A. Searles; Ryan T. Glasser; Brian T. Kirby (CoRR, 2021)

Machine learning pipeline for quantum state estimation with incomplete measurements. - Onur Danaci; Sanjaya Lohani; Brian T. Kirby; Ryan T. Glasser (Mach. Learn. Sci. Technol., 2021)

Demonstration of machine-learning-enhanced Bayesian quantum state estimation. - Sanjaya Lohani; Joseph M. Lukens; Atiyya A. Davis; Amirali Khannejad; Sangita Regmi; Daniel E. Jones; Ryan T. Glasser; Thomas A. Searles; Brian T. Kirby (CoRR, 2022)

Data-centric machine learning in quantum information science. - Sanjaya Lohani; Joseph M. Lukens; Ryan T. Glasser; Thomas A. Searles; Brian T. Kirby (Mach. Learn. Sci. Technol., 2022)

Dimension-adaptive machine learning-based quantum state reconstruction. - Sanjaya Lohani; Sangita Regmi; Joseph M. Lukens; Ryan T. Glasser; Thomas A. Searles; Brian T. Kirby (Quantum Mach. Intell., 2023)

Deep learning for enhanced free-space optical communications. - Manon P. Bart; Nicholas J. Savino; Paras Regmi; Lior Cohen; Haleh Safavi; Harry C. Shaw; Sanjaya Lohani; Thomas A. Searles; Brian T. Kirby; Hwang Lee; Ryan T. Glasser (Mach. Learn. Sci. Technol., 2023)

SMC Is All You Need: Parallel Strong Scaling. - Xinzhu Liang; Sanjaya Lohani; Joseph M. Lukens; Brian T. Kirby; Thomas A. Searles; Kody J. H. Law (CoRR, 2024)

Scalable Bayesian Monte Carlo: fast uncertainty estimation beyond deep ensembles. - Xinzhu Liang; Joseph M. Lukens; Sanjaya Lohani; Brian T. Kirby; Thomas A. Searles; Xin Qiu; Kody J. H. Law (CoRR, 2025)