PGM-Lab / probabilisticAI_tutorials
Repo for the Tutorials of Day1-Day3 of the Nordic Probabilistic AI School 2019 (https://2019.probabilistic.ai/)
☆20Updated 5 years ago
Alternatives and similar repositories for probabilisticAI_tutorials:
Users that are interested in probabilisticAI_tutorials are comparing it to the libraries listed below
- Code for paper "Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation"☆31Updated 5 years ago
- Mixture Density Networks (Bishop, 1994) tutorial in JAX☆59Updated 4 years ago
- Code for Unbiased Implicit Variational Inference (UIVI)☆14Updated 6 years ago
- ☆26Updated 5 years ago
- Materials of the Nordic Probabilistic AI School 2019.☆129Updated 4 years ago
- Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen☆25Updated 4 years ago
- BIVA: A Very Deep Hierarchy of Latent Variables forGenerative Modeling☆29Updated 5 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆98Updated last year
- Discontinuous Hamiltonian Monte Carlo in JAX☆41Updated 5 years ago
- PyTorch implementation of AVF☆45Updated 4 years ago
- Train neural networks to use as SMC and importance sampling proposals☆24Updated 7 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 7 years ago
- ☆11Updated 8 years ago
- A collection of Gaussian process models☆30Updated 7 years ago
- ☆64Updated 6 years ago
- Repository of models in Pyro☆29Updated 8 months ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 5 years ago
- This repository houses the code for the community website http://www.probabilistic-numerics.org☆35Updated 4 years ago
- Jupyter Notebook corresponding to 'Going with the Flow: An Introduction to Normalizing Flows'☆25Updated 3 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 3 years ago
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 3 years ago
- Library for learning and inference with Sum-product Networks utilizing TensorFlow 2.x and Keras☆48Updated 3 years ago
- NeurIPS 2018. Linear-time model comparison tests.☆18Updated 5 years ago
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 6 years ago
- ☆59Updated 6 years ago
- Python 3.7 version of David Barber's MATLAB BRMLtoolbox☆24Updated 6 years ago
- Short Course on Optimization for Machine Learning - Slides and Practical Labs - DS3 Data Science Summer School, June 24 to 28, 2019, Pari…☆20Updated 5 years ago
- Open access book on variational Bayesian methods written collaboratively☆28Updated 9 years ago
- ☆37Updated 5 years ago