fabianp / overview_optalgsLinks
☆30Updated 5 years ago
Alternatives and similar repositories for overview_optalgs
Users that are interested in overview_optalgs are comparing it to the libraries listed below
Sorting:
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 years ago
- A Python library for reinforcement learning using Bayesian approaches☆53Updated 10 years ago
- Columbia Advanced Machine Learning Seminar☆24Updated 7 years ago
- Repo for a paper about constructing priors on very deep models.☆73Updated 9 years ago
- A Python convex optimization package using proximal splitting methods☆119Updated 3 months ago
- ☆67Updated 7 years ago
- Implementation of stochastic variational inference for Bayesian hidden Markov models.☆67Updated 8 years ago
- Edward content including papers, posters, and talks☆92Updated 5 years ago
- Implementation of Hamiltonian Monte Carlo using Google's TensorFlow☆46Updated 10 years ago
- A Newton ADMM based solver for Cone programming.☆39Updated 8 years ago
- Fastidious accounting of entropy streams into and out of optimization and sampling algorithms.☆33Updated 9 years ago
- Lasagne / Theano tutorials for Nvidia Deep Learning Summercamp 2016☆26Updated 9 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 9 years ago
- This code accompanies the proximity variational inference paper.☆18Updated 6 years ago
- Exponential Machines implementation☆42Updated 9 months ago
- TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network☆183Updated 7 years ago
- This repository houses the code for the community website http://www.probabilistic-numerics.org☆36Updated 5 years ago
- Examples of building probabilistic models with MXNet linear algebra operators☆23Updated 8 years ago
- Advances in Approximate Bayesian Inference Symposium☆50Updated 2 weeks ago
- Collaborative filtering with the GP-LVM☆25Updated 10 years ago
- Kohonen vector quantizers (SOM, NG, GNG)☆71Updated 7 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 6 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 7 years ago
- Structure learning for sparse graphs with latent variables☆45Updated 9 years ago
- Experiments in Bayesian Machine Learning☆69Updated 6 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆64Updated 7 years ago
- Matlab code implementing Minimum Probability Flow Learning.☆69Updated 11 years ago
- Python implementation of Markov Jump Hamiltonian Monte Carlo☆24Updated 8 years ago
- Backpropagate derivatives through the Cholesky decomposition☆59Updated 5 years ago