ebonilla / AutoGPLinks
Code for AutoGP
☆27Updated 6 years ago
Alternatives and similar repositories for AutoGP
Users that are interested in AutoGP are comparing it to the libraries listed below
Sorting:
- Code repository for the generalized Galton board example in the paper "Mining gold from implicit models to improve likelihood-free infere…☆33Updated 5 years ago
- Variational Fourier Features☆85Updated 4 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 years ago
- A collection of Gaussian process models☆30Updated 8 years ago
- Additional kernels that can be used with scikit-learn's Gaussian Process module☆82Updated last year
- Neural Processes implementation for 1D regression☆65Updated 6 years ago
- ☆40Updated 6 years ago
- Stochastic Gradient Riemannian Langevin Dynamics☆34Updated 10 years ago
- Particle Gibbs for Bayesian Additive Regression Trees☆33Updated 10 years ago
- ABCpy package☆115Updated last year
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆150Updated 6 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Bayesian GPLVM in MATLAB and R☆75Updated 8 years ago
- ☆26Updated 7 years ago
- Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.☆33Updated 8 years ago
- Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.☆82Updated 5 years ago
- TensorFlow implementation for training MCMC samplers from the paper: Generalizing Hamiltonian Monte Carlo with Neural Network☆183Updated 7 years ago
- Convolutional Gaussian processes based on GPflow.☆95Updated 7 years ago
- A library of scalable Bayesian generalised linear models with fancy features☆60Updated 7 years ago
- Pareto smoothed importance sampling (PSIS) and PSIS leave-one-out cross-validation for Python and Matlab/Octave☆77Updated last year
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 7 years ago
- A Gaussian process toolbox in python☆42Updated 13 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- Open Data Science☆33Updated 8 months ago
- Implementation of the Gaussian Process Autoregressive Regression Model☆67Updated 7 months ago
- Code for the paper 'Efficient Variational Inference for Gaussian Process Regression Networks'☆22Updated 11 years ago
- Implementation of an algorithm for Markov chain Monte Carlo with data subsampling☆32Updated 9 years ago
- Python package for inference with Gaussian processes☆11Updated 10 years ago
- Look Ahead Hamiltonian Monte Carlo☆30Updated 10 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago