philipk01 / Optimization_and_Sampling_for_Bayesian_Inference
Adaptive MCMC and CMA-ES Python code
☆14Updated 5 years ago
Alternatives and similar repositories for Optimization_and_Sampling_for_Bayesian_Inference:
Users that are interested in Optimization_and_Sampling_for_Bayesian_Inference are comparing it to the libraries listed below
- Nonparametric Differential Equation Modeling☆53Updated last year
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Gaussian processes regression models with linear inequality constraints☆14Updated 9 months ago
- Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features☆23Updated 6 years ago
- Unifying sparse approximations for Gaussian process regression and classification, using Power EP☆22Updated 8 years ago
- Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"☆26Updated 6 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆27Updated last year
- Parametric Gaussian Process Regression for Big Data☆44Updated 5 years ago
- Heterogeneous Multi-output Gaussian Processes☆52Updated 4 years ago
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆30Updated 9 months ago
- Methods and experiments for assumed density SDE approximations☆11Updated 3 years ago
- Learning unknown ODE models with Gaussian processes☆26Updated 6 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 6 years ago
- Python and MATLAB code for Stein Variational sampling methods☆25Updated 5 years ago
- Library for Deep Gaussian Processes based on GPflow☆19Updated 5 years ago
- Multi-Information Source Optimization☆22Updated 5 years ago
- Continual Gaussian Processes☆32Updated last year
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- 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
- The code in this repository follows the paper "Stochastic gradient MCMC"☆26Updated 5 years ago
- ☆30Updated 2 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆38Updated 5 years ago
- Modular Gaussian Processes☆15Updated 3 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆72Updated 4 years ago
- Variational Gaussian Process State-Space Models☆23Updated 9 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 5 years ago
- ☆29Updated 2 years ago
- ☆28Updated 6 years ago
- Code for Randomly Projected Additive Gaussian Processes☆25Updated 5 years ago