leewayhertz

Bayesian networks in AI: Role in machine learning, example, types and applications

Imagine a scenario where a team of doctors faces a perplexing medical puzzle. A patient shows a range of symptoms, each pointing to multiple possible diseases. How can they navigate this diagnostic ...
note

[Udemy] The Ultimate Learning Method a Researcher Found After Struggling to Stick with Python

I have had the experience of letting dozens of programming books pile up unread. Haven't you all had that experience too? I would think, "I'll read it this week," but as soon as experiments piled up, ...
IEEE

Bayesian Neural Networks via MCMC: A Python-Based Tutorial

Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...
GitHub

PyVBMC: Variational Bayesian Monte Carlo in Python

PyVBMC is a Python implementation of the Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference, previously implemented in MATLAB. VBMC is an approximate inference method ...
C&EN

Characterization of Integrase and Excisionase Activity in a Cell-Free Protein Expression System Using a Modeling and Analysis Pipeline

Biology and Biological Engineering, California Institute of Technology, Pasadena, California91125, United States Control and Dynamical Systems, California Institute of Technology, Pasadena, ...
Frontiers

Bayesian Generalized Linear Model for Simulating Bacterial Inactivation/Growth Considering Variability and Uncertainty

Predictive microbiology models explain bacterial number variations over time and how growth/inactivation rates are affected by environmental conditions (Lammerding and Fazil, 2000). In the development ...