paulorauber / pgm
Probabilistic graphical models in python
☆22Updated 5 years ago
Related projects: ⓘ
- Dirichlet Process K-means☆46Updated 3 months ago
- Practice with MCMC methods and dynamics (Langevin, Hamiltonian, etc.)☆43Updated 4 years ago
- State space modeling with recurrent neural networks☆42Updated 6 years ago
- Implementation of stochastic variational inference for Bayesian hidden Markov models.☆65Updated 7 years ago
- Edward content including papers, posters, and talks☆90Updated 3 years ago
- Open access book on variational Bayesian methods written collaboratively☆28Updated 9 years ago
- Experiments in Bayesian Machine Learning☆67Updated 5 years ago
- TensorFlow implementation of Bayes-by-Backprop algorithm from "Weight Uncertainty in Neural Networks" paper☆51Updated 5 years ago
- Inference and Representation (DS-GA-1005, CSCI-GA.2569), fall 18☆62Updated 5 years ago
- An implementation of "Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles" (http://arxiv.org/abs/1612.01474)☆34Updated 7 years ago
- Python implementation of the PR-SSM.☆51Updated 6 years ago
- Variational Fourier Features☆81Updated 3 years ago
- ☆69Updated 6 years ago
- Variational inference for Dirichlet process mixture models with multinomial mixture components.☆32Updated 10 years ago
- Python 3.7 version of David Barber's MATLAB BRMLtoolbox☆24Updated 6 years ago
- Gaussian Processes in Pytorch☆74Updated 4 years ago
- PyData San Luis 2017 Tutorial: An Introduction to Gaussian Processes in PyMC3☆15Updated 6 years ago
- Code to related to my NIPS 2016 paper☆10Updated 7 years ago
- Repo for a paper about constructing priors on very deep models.☆69Updated 8 years ago
- Public repository for the work on bandit problems☆23Updated 5 months ago
- ☆55Updated this week
- Gaussian Process and Uncertainty Quantification Summer School 2017☆26Updated last year
- Neural Processes implementation for 1D regression☆65Updated 5 years ago
- Hierarchical Mixture of Experts,Mixture Density Neural Network☆45Updated 7 years ago
- Material for my Caltech tutorial on deep learning and tensor methods☆69Updated 5 years ago
- A Python library for reinforcement learning using Bayesian approaches☆51Updated 9 years ago
- ☆28Updated 4 years ago
- ☆63Updated 6 years ago
- Code for Implementation, Inference, and Learning of Bayesian and Markov Networks along with some practical examples.☆104Updated 11 years ago
- Columbia Advanced Machine Learning Seminar☆24Updated 6 years ago