florist-notes / CS228_PGM
π² Stanford CS 228 - Probabilistic Graphical Models
β106Updated 2 months ago
Related projects β
Alternatives and complementary repositories for CS228_PGM
- π Stanford CS 228 - Probabilistic Graphical Modelsβ118Updated 5 years ago
- This repository contains my implementation of the programming assignments of Probabilistic Graphical Models delivered by Stanford Universβ¦β32Updated 7 years ago
- π Stanford CS 228 - Probabilistic Graphical Modelsβ68Updated 5 years ago
- β174Updated last year
- β210Updated last year
- Material for the "Probabilistic Machine Learning" Course at the University of TΓΌbingen, Summer Term 2023β131Updated last year
- β70Updated last year
- MPhil Machine Learning and Machine Intelligence @ University of Cambridgeβ44Updated 5 years ago
- A curated list of awesome variational inferenceβ18Updated 4 years ago
- Solutions to "Machine Learning: A Probabilistic Perspective"β153Updated 3 years ago
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831β35Updated last year
- My lecture notes during times at UCL.β28Updated 3 years ago
- References at the Intersection of Causality and Reinforcement Learningβ88Updated 4 years ago
- Materials of the Nordic Probabilistic AI School 2023.β86Updated last year
- β39Updated 2 years ago
- My solutions to problems of The Elements of Statistical Learning by Profs. Hastie, Tibshirani, and Friedman.β91Updated 5 years ago
- My notes from classβ59Updated 6 years ago
- DiBS: Differentiable Bayesian Structure Learning, NeurIPS 2021β46Updated 8 months ago
- Repo for the Tutorials of Day1-Day3 of the Nordic Probabilistic AI School 2021 (https://probabilistic.ai/)β47Updated 3 years ago
- PRML notes, proofs and algorithms implemented in Pythonβ30Updated 2 months ago
- Amortized Inference for Causal Structure Learning, NeurIPS 2022β54Updated 8 months ago
- Materials of the Nordic Probabilistic AI School 2021.β93Updated 3 years ago
- Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, caβ¦β162Updated 6 months ago
- β175Updated 2 weeks ago
- paper lists and information on mean-field theory of deep learningβ75Updated 5 years ago
- The collection of papers about combining deep learning and Bayesian nonparametricsβ118Updated 5 years ago
- Complete solutions for exercises and MATLAB example codes for "Machine Learning: A Probabilistic Perspective" 1/e by K. Murphyβ235Updated 4 years ago
- CS 7301: Spring 2021 Course on Advanced Topics in Optimization in Machine Learningβ174Updated 3 years ago
- DS-GA 3001: Tools and Techniques for Machine Learning (NYU Fall 2021)β43Updated 10 months ago
- Course notesβ621Updated 6 months ago