Applying SVGD to Bayesian Neural Networks for Cyclical Time-Series Prediction and Inference

no code implementations • 17 Jan 2019 • Xinyu Hu, Paul Szerlip, Theofanis Karaletsos, Rohit Singh

A regression-based BNN model is proposed to predict spatiotemporal quantities like hourly rider demand with calibrated uncertainties.

regression Time Series +1

Pyro: Deep Universal Probabilistic Programming

1 code implementation • 18 Oct 2018 • Eli Bingham, Jonathan P. Chen, Martin Jankowiak, Fritz Obermeyer, Neeraj Pradhan, Theofanis Karaletsos, Rohit Singh, Paul Szerlip, Paul Horsfall, Noah D. Goodman

Pyro is a probabilistic programming language built on Python as a platform for developing advanced probabilistic models in AI research.

Probabilistic Programming Variational Inference

A Proposed Infrastructure for Adding Online Interaction to Any Evolutionary Domain

no code implementations • 11 Jul 2014 • Paul Szerlip, Kenneth O. Stanley

To address the difficulty of creating online collaborative evolutionary systems, this paper presents a new prototype library called Worldwide Infrastructure for Neuroevolution (WIN) and its accompanying site WIN Online (http://winark. org/).