2 papers
cs.LG2024
Scalable Spatiotemporal Prediction with Bayesian Neural Fields
Feras Saad, Jacob Burnim, Colin Carroll +4
Spatiotemporal datasets, which consist of spatially-referenced time series, are ubiquitous in diverse applications, such as air pollution monitoring, disease tracking, and cloud-de…
stat.CO2024
Running Markov Chain Monte Carlo on Modern Hardware and Software
Pavel Sountsov, Colin Carroll, Matthew D. Hoffman
Today, cheap numerical hardware offers huge amounts of parallel computing power, much of which is used for the task of fitting neural networks to data. Adoption of this hardware to…