4 citations · 4 across the 1 of their papers we have counts for
2 papers
cs.LG2019★ 4 cited
Applying SVGD to Bayesian Neural Networks for Cyclical Time-Series Prediction and Inference
Xinyu Hu, Paul Szerlip, Theofanis Karaletsos +1
A regression-based BNN model is proposed to predict spatiotemporal quantities like hourly rider demand with calibrated uncertainties. The main contributions of this paper are (i) A…
cs.LG2018
Pyro: Deep Universal Probabilistic Programming
Eli Bingham, Jonathan P. Chen, Martin Jankowiak +7
Pyro is a probabilistic programming language built on Python as a platform for developing advanced probabilistic models in AI research. To scale to large datasets and high-dimensio…