3 papers
stat.ML2025
Scalable Bayesian Monte Carlo: fast uncertainty estimation beyond deep ensembles
Xinzhu Liang, Joseph M. Lukens, Sanjaya Lohani +4
This work introduces a new method designed for Bayesian deep learning called scalable Bayesian Monte Carlo (SBMC). The method is comprised of a model and an algorithm. The model in…
stat.ML2025
Comparison of parallel SMC and MCMC for Bayesian deep learning
Xinzhu Liang, Joseph M. Lukens, Sanjaya Lohani +4
This work systematically compares parallel implementations of consistent (asymptotically unbiased) Bayesian deep learning algorithms: sequential Monte Carlo sampler (SMC$_\parallel…
physics.ed-ph2024
Outcomes from a Workshop on a National Center for Quantum Education
Edwin Barnes, Michael B. Bennett, Alexandra Boltasseva +35
In response to numerous programs seeking to advance quantum education and workforce development in the United States, experts from academia, industry, government, and professional…