Dr. Enrique ter Horst, “A Bayesian time varying approach to risk neutral density estimation”

Who: Dr. Enrique ter Horst, Universidad de los Andes, Bogotá, Colombia What: “A Bayesian time varying approach to risk neutral density estimation.” When: Friday November 4th, 4PM Where: Beaupre 105 Abstract: We expand the literature of risk neutral density estimation across maturities from implied volatility curves, which are usually estimated and interpolated through cubic smoothing […]

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Dr. Noah M. Daniels, URI – Manifold Mapping Enables Fast Search, Anomaly Detection, and More

Join us for our Computer Science and Statistics Colloquium Series. When: Friday, Oct 28th, 4PM Where: Beaupre 105 Speaker: Dr. Noah M. Daniels, URI Title: Manifold Mapping Enables Fast Search, Anomaly Detection, and More Most likely, you have heard the term “Big Data.” The world has been experiencing an explosive growth in data, and that […]

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Dr. Lorin Crawford, Microsoft Research New England and Brown University

Variable Selection and Prioritization in Bayesian Machine Learning Methods Where: Beaupre 105 When: Friday, October 21st, 4PM Abstract: A consistent theme of the work done in my lab group is to take modern computational approaches and develop theory that enable their interpretations to be related back to classical genomic principles. The central aim of this […]

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Dr. Roberta De Vito, Brown University

Multi-Study Approaches: adventures from nutrition to genomics Date: September 30th, 2022 @ 4pm-5pm Location: Beaupre 105 Host: Gavino Puggione Biostatistics and computational biology are increasingly facing the urgent challenge of efficiently dealing with a large amount of experimental data. High-throughput assays are transforming the study of biology, as they generate a rich, complex, and diverse […]

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Derek Aguiar

Bayesian nonparametric modelling and scalable inference in genomics and transcriptomics data Date: November 19th, 2021 @ 3pm-4pm Location: Beaupre Center for Chemical & Forensic Sciences. Room 105 Host: Noah Daniels   

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