alphabetakappa / Probabilistic-Graphical-Models-MaterialsLinks
☆33Updated 6 years ago
Alternatives and similar repositories for Probabilistic-Graphical-Models-Materials
Users that are interested in Probabilistic-Graphical-Models-Materials are comparing it to the libraries listed below
Sorting:
- 🌀 Stanford CS 228 - Probabilistic Graphical Models☆89Updated 6 years ago
 - Solutions for David Barber's "Bayesian Reasoning and Machine Learning" Book☆24Updated 4 years ago
 - ☆54Updated last year
 - 🌲 Stanford CS 228 - Probabilistic Graphical Models☆145Updated last year
 - ☆88Updated 2 years ago
 - My solutions to problems of The Elements of Statistical Learning by Profs. Hastie, Tibshirani, and Friedman.☆90Updated 6 years ago
 - ☆236Updated 2 years ago
 - Solutions to the problems in the book: Linear Algebra and Learning from Data by Gilbert Strang, MIT☆297Updated 3 years ago
 - ☆190Updated 2 years ago
 - This is a companion to the ‘Mathematical Foundations’ section of the book, Mathematics for Machine Learning by Marc Deisenroth, Aldo Fais…☆294Updated 4 years ago
 - ☆37Updated 4 months ago
 - 🌀 Stanford CS 228 - Probabilistic Graphical Models☆122Updated 6 years ago
 - Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, ca…☆176Updated last year
 - PRML notes, proofs and algorithms implemented in Python☆38Updated this week
 - Repository for my Big Data Optimization course☆35Updated 4 years ago
 - Matlab Notebook for visualizing random matrix theory results and their applications to machine learning☆130Updated 2 years ago
 - Solutions to Wasserman's 'All of Statistics'.☆104Updated 6 years ago
 - My solutions to DLFC - Deep Learning: Foundations and Concepts☆91Updated 7 months ago
 - Repository for ML in Practice Course at CMU (10-718)☆67Updated this week
 - Berkeley CS182/282A Designing, Visualizing and Understanding Deep Neural Networks☆85Updated 2 years ago
 - Implementation of different diffusion models for probabilistic image generation☆38Updated last year
 - Material for the "Probabilistic Machine Learning" Course at the University of Tübingen, Summer Term 2023☆188Updated 2 years ago
 - A (concise) curated list of awesome Causal Inference resources.☆244Updated 3 years ago
 - Python & Matlab code for the figures from the book "Learning Theory from First Principles" by Francis Bach☆127Updated last year
 - Code associated with my Interpretable AI Book (https://www.manning.com/books/interpretable-ai)☆64Updated 3 years ago
 - Notes + notebooks on EM + variational EM algorithms for Bayesian methods tutorial☆41Updated 7 years ago
 - A curated list of awesome work on causal inference, particularly in machine learning.☆108Updated 4 years ago
 - ☆29Updated 6 years ago
 - Interactive textbook on state-space models☆197Updated last year
 - A curated list of awesome deep causal learning methods since 2018☆18Updated 2 years ago