vr308 / GPLVMLinks
Implementation of GPLVM and Bayesian GPLVM in pytorch/gpytorch
☆15Updated 4 years ago
Alternatives and similar repositories for GPLVM
Users that are interested in GPLVM are comparing it to the libraries listed below
Sorting:
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods☆22Updated last year
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- ☆15Updated 2 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆20Updated 3 years ago
- ☆30Updated 2 years ago
- Combining smooth constraint for building DAG with normalizing flow in order to replace autoregressive transformations while keeping tract…☆45Updated last year
- Code for efficiently sampling functions from GP(flow) posteriors☆72Updated 4 years ago
- Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design☆35Updated 4 years ago
- Minimal Gaussian process library in JAX with a simple (custom) approach to state management.☆12Updated last year
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 3 years ago
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 4 years ago
- Library for Bayesian Quadrature☆32Updated 6 years ago
- [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)☆22Updated 4 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆24Updated 2 years ago
- Bayesian Optimization with Density-Ratio Estimation☆24Updated 2 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Re-Examining Linear Embeddings for High-dimensional Bayesian Optimization☆41Updated 3 years ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 7 years ago
- Course Website☆9Updated 3 years ago
- A community repository for benchmarking Bayesian methods☆11Updated 2 years ago
- PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆48Updated 4 years ago
- ☆52Updated 2 years ago
- Nonparametric Differential Equation Modeling☆54Updated last year
- Code to minimize the Variational Contrastive Divergence (VCD)☆29Updated 6 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆57Updated 4 years ago
- Random feature latent variable models in Python☆22Updated 2 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago