This article is a Python copying activity record of Chapter 9, Part 3: 'Logistic Regression Model' from the book 'Introduction to Data Analysis with Bayesian Statistical Modeling using R and Stan'.
I work in materials development at a chemical manufacturer and spend my days thinking about how to apply AI to research. In this note, I have been writing a series on the theme of "Self-Driving Labs ...
Aether AI, founded by UCSD professor Biwei Huang, closed a $20 million seed round on June 18, 2026 to build causal world models that understand cause-and-effect relationships rather than statistical ...
This important work introduces an integrated open-source platform for behavioral acquisition and pose estimation that substantially improves the accessibility and speed of real-time animal tracking ...
As part of mid-century net-zero carbon neutrality pathways, sustainable aviation fuels (SAFs) constitute the only viable decarbonization strategy for commercial aviation in the foreseeable future.
Software is a set of computer instructions and can refer to executable programs, scripts and libraries. By using deep learning sequence models, we predict non-coding variant effects across the allele ...
Abstract: This article proposes a robust topology change-aware distribution system state estimation (DSSE) method based on a physics-informed graph neural network and Bayesian Probability Weighted ...
End-to-end A/B test analysis for a (fictional) streaming subscription product. Demonstrates the full product data scientist workflow: experiment design, data quality, frequentist & Bayesian analysis, ...
Bayesian frameworks directly address these challenges by providing (1) uncertainty quantification and (2) sample-efficient exploration of sequence space. BayeStab couples graph features with ...
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