gianlucadetommaso / Stein-variational-samplersLinks
Python and MATLAB code for Stein Variational sampling methods
☆25Updated 6 years ago
Alternatives and similar repositories for Stein-variational-samplers
Users that are interested in Stein-variational-samplers are comparing it to the libraries listed below
Sorting:
- Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"☆18Updated 4 years ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 5 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 7 years ago
- ☆29Updated 2 years ago
- Black Box Variational Inference☆14Updated 10 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- Nonparametric Differential Equation Modeling☆53Updated last year
- Codes for "Understanding and Accelerating Particle-Based Variational Inference" (ICML-19)☆22Updated 5 years ago
- Matlab code implementing Hamiltonian Annealed Importance Sampling for importance weight, partition function, and log likelihood estimatio…☆26Updated 10 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- Unifying sparse approximations for Gaussian process regression and classification, using Power EP☆22Updated 8 years ago
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 6 years ago
- Modular Gaussian Processes☆15Updated 3 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- ☆40Updated 6 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆39Updated 6 years ago
- Gaussian processes with PyTorch☆30Updated 3 years ago
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆32Updated 11 months ago
- Parametric Gaussian Process Regression for Big Data☆45Updated 5 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Methods and experiments for assumed density SDE approximations☆12Updated 3 years ago
- see https://github.com/thangbui/geepee for a faster implementation☆37Updated 8 years ago
- Bayesian Deep Learning with Stochastic Gradient MCMC Methods☆39Updated 3 years ago
- ☆30Updated 2 years ago
- ☆26Updated 7 years ago
- Provides various extensions to the GPML toolbox for Gaussian process inference in MATLAB.☆32Updated 8 years ago
- Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features☆23Updated 6 years ago
- Sparse Orthogonal Variational Inference for Gaussian Processes (SOLVE-GP)☆22Updated 3 years ago