philipphennig / ProbML_AppsLinks
Apps (mostly streamlit) for the "Probabilistic Machine Learning" Lecture course at the University of Tübingen
☆27Updated last year
Alternatives and similar repositories for ProbML_Apps
Users that are interested in ProbML_Apps are comparing it to the libraries listed below
Sorting:
- Material for the "Probabilistic Machine Learning" Course at the University of Tübingen, Summer Term 2023☆167Updated last year
- Notes for the Numerics of Machine Learning Lecture Course at the University of Tübingen☆210Updated last year
- Materials related to the 2024-2025 mini course on Probabilistic Models and Bayesian Methods at the Faculty of Finance at Kharazmi Univers…☆23Updated last month
- Course 5SSD0 - Bayesian Machine Learning and Information Processing☆48Updated 3 months ago
- Utilities for probabilistic ML☆36Updated last year
- Materials of the Nordic Probabilistic AI School 2024.☆66Updated last year
- Neat Bayesian machine learning examples☆58Updated 2 weeks ago
- Materials of the Nordic Probabilistic AI School 2022.☆181Updated 2 years ago
- Following along with Statistical Rethinking text on Bayesian modeling by McElreath☆64Updated 4 years ago
- Advanced LTCC course in StatisticsThis course will provide an overview of Monte Carlo methods when used for problems in Statistics. After…☆27Updated 2 years ago
- Data Science for Dynamical System Course☆122Updated 9 months ago
- Structural Time Series in JAX☆193Updated last year
- Tutorial materials of the Probabilistic Numerics Spring School.☆34Updated 2 years ago
- Toolbox for working with streaming data as rough paths in Python☆36Updated 2 weeks ago
- IterGP: Computation-Aware Gaussian Process Inference (NeurIPS 2022)☆42Updated 2 years ago
- Recursive Bayesian Estimation (Sequential / Online Inference)☆59Updated last year
- Introduction to Gaussian Processes☆29Updated 7 years ago
- Course material for the PhD course in Advanced Bayesian Learning☆59Updated 4 months ago
- Tutorials and sampling algorithm comparisons☆75Updated this week
- Public code for running Stochastic Gradient Descent on GPs.☆39Updated 2 months ago
- Supporting material for Princeton ORF522☆13Updated 7 months ago
- Neural parameter calibration for multi-agent models. Uses neural networks to estimate marginal densities on parameters and networks☆30Updated last week
- A simple library to run variational inference on Stan models.☆32Updated 2 years ago
- PyVBMC: Variational Bayesian Monte Carlo algorithm for posterior and model inference in Python☆120Updated 5 months ago
- ☆11Updated 2 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆42Updated 11 months ago
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆233Updated last year
- Gaussian Processes and Statistical Decision-making in Non-Euclidean Spaces☆199Updated 3 years ago
- Adaptive MCMC and CMA-ES Python code☆14Updated 5 years ago
- A Python package for probabilistic state space modeling with JAX☆838Updated 2 months ago