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Research / archived / 2025

Generative Model

A course and knowledge archive for probabilistic graphical models, deep generative models, readings, and notes.

HTML PGM Generative Models Notes Readings
GitHub
Audiofool934/Generative-Model
Language
HTML
Stars
0
Last Push
2025.03.31
README Sync
2026.05.30
[ Project Brief ]

Overview

Generative Model is a study archive for probabilistic graphical models and deep generative models.

It collects course material, notes, readings, and conceptual maps around generation: graphical models, discriminative versus generative framing, and the older foundations behind modern creative AI systems.

Archive Role

On audiofool.blog, this project works as a provenance object. It records the learning path behind later music-generation work: MUSE, T2M, MERIC, WeaveWave, and MultiTake all sit downstream from this foundation.

[ Synced from GitHub README ]

Repository Document

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Generative Model

Courses

Chongxuan Li - Probabilistic Graphical Models: Principles and Applications

Daphne Koller - Probabilistic Graphical Models Specialization

Knowledges

Generation(overview)

Probabilistic Graphical Models

Deep Generative Models

Notes

Generative-vs-Discriminative

Readings

An Introduction to Probabilistic Graphical Models

Probabilistic Graphical Models Principles and Applications