Sanjaya Lohani

According to our database, Sanjaya Lohani authored at least 15 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

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, May, 2025

Potential of Distributed Circuits for Mitigating Quantum Image Noise.

Yayu Mo, Mitchell A. Thornton, Sanjaya Lohani

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2025

Analyzing Quantum Noise in Image Encodings: A Circuit-Based Hybrid Integration Approach.

Yayu Mo, Mitchell A. Thornton, Sanjaya Lohani

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2025

2024

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

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., December, 2023

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

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., December, 2022

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

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

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

2020

Machine learning assisted quantum state estimation.

Sanjaya Lohani, Brian T. Kirby, Michael Brodsky, Onur Danaci, Ryan T. Glasser

Mach. Learn. Sci. Technol., 2020

Coherent optical communications enhanced by machine intelligence.

Sanjaya Lohani, Ryan T. Glasser

Mach. Learn. Sci. Technol., 2020

On the experimental feasibility of quantum state reconstruction via machine learning.

Sanjaya Lohani, Thomas A. Searles, Brian T. Kirby, Ryan T. Glasser

CoRR, 2020

2019

Dispersion Characterization and Pulse Prediction with Machine Learning.

Sanjaya Lohani, Erin M. Knutson, Wenlei Zhang, Ryan T. Glasser

CoRR, 2019

Generative Machine Learning for Robust Free-Space Communication.

Sanjaya Lohani, Ryan T. Glasser

CoRR, 2019