Probabilistic Modeling

Model Perspective

Jul 19, 2024 · Artificial Intelligence

Can Bayesian Networks Predict Public Opinion Reversals? A Practical Guide

This article explains how Bayesian Network models can be built and applied to forecast public opinion reversals, detailing the network structure, joint probability distribution, inference methods, and a Python implementation using pgmpy with sample data and analysis of key influencing factors.

Bayesian NetworkProbabilistic ModelingPublic Opinion

0 likes · 10 min read

Can Bayesian Networks Predict Public Opinion Reversals? A Practical Guide

DevOps

Apr 7, 2023 · Artificial Intelligence

Understanding How ChatGPT Generates Answers: Probabilistic Language Modeling and Word Vectors

The article explains that ChatGPT produces responses by converting words into high‑dimensional vectors, feeding them through neural networks, and selecting tokens based on probability distributions, while also contrasting GPT with BERT and describing a related training event.

ChatGPTGPT-4NLP

0 likes · 7 min read

Understanding How ChatGPT Generates Answers: Probabilistic Language Modeling and Word Vectors

Model Perspective

Oct 15, 2022 · Fundamentals

Unlock Faster Bayesian Sampling: How Hamiltonian Monte Carlo Works

Hamiltonian Monte Carlo (HMC) is a rapid sampling technique that improves upon traditional MCMC by leveraging Hamiltonian dynamics, using position and velocity to define potential and kinetic energy, and follows a series of steps—including momentum sampling, leapfrog integration, and Metropolis acceptance—to efficiently explore complex probability distributions.

Bayesian SamplingHamiltonian Monte CarloMCMC

0 likes · 4 min read

Unlock Faster Bayesian Sampling: How Hamiltonian Monte Carlo Works