Implement Logistic Regression in Python from Scratch ! In this video, we will implement Logistic Regression in Python from ...

Abstract: This study examines logit models applied to the truck route choice problem using GPS trucking data from the Dallas metropolitan area. Instead of assuming a constant coefficient for each ...

Williams, A. and Louis, L. (2026) Cumulative Link Modeling of Ordinal Outcomes in the National Health Interview Survey Data: Application to Depressive Symptom Severity. Journal of Data Analysis and ...

In this work we present two main contributions: the first one is a Python implementation of the discrete approximation of the Laplace-Beltrami operator (LBO) (Belkin et al., 2008) allowing us to solve ...

Depending on the position, the summer job can last for 3- 4 months and is carried out between May and September 2026. Please note that these summer job positions are available for B.Sc. or M.Sc.

Abstract: Sparse Bayesian learning (SBL) is an algorithm for high-dimensional data processing based on Bayesian statistical theory. Its goal is to improve the generalization ability and efficiency of ...

The PyRenew package is a flexible tool for simulation and statistical inference of epidemiological models, emphasizing renewal models. Built on top of the numpyro Python library, pyrenew provides core ...

Code for the paper "Sequential Bayesian Experimental Design for Implicit Models via Mutual Information", Bayesian Analysis 2021, https://arxiv.org/abs/2003.09379.

Microsoft has added official Python support to Aspire 13, expanding the platform beyond .NET and JavaScript for building and running distributed apps. Documented today in a Microsoft DevBlogs post, ...