secondmind-labs / bayesian_benchmarks
A community repository for benchmarking Bayesian methods
☆11Updated last year
Alternatives and similar repositories for bayesian_benchmarks:
Users that are interested in bayesian_benchmarks are comparing it to the libraries listed below
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆30Updated 8 months ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆41Updated 7 months ago
- Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design☆30Updated 3 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆19Updated 3 years ago
- ☆15Updated 2 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- ☆30Updated 2 years ago
- code for BINOCULARS and Multi-Step BO☆11Updated 4 years ago
- [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)☆21Updated 4 years ago
- Source for experiments in the Additive Gaussian process paper, as well as extensions relating to dropout.☆21Updated 11 years ago
- Implementation of GPLVM and Bayesian GPLVM in pytorch/gpytorch☆15Updated 3 years ago
- Online variational GPs☆31Updated last year
- Kernel Identification Through Transformers☆12Updated last year
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 5 years ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 5 years ago
- Minimal Gaussian process library in JAX with a simple (custom) approach to state management.☆11Updated last year
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 3 years ago
- Python and MATLAB code for Stein Variational sampling methods☆24Updated 5 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆70Updated 4 years ago
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 3 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆38Updated 5 years ago
- Re-Examining Linear Embeddings for High-dimensional Bayesian Optimization☆41Updated 3 years ago
- Nonparametric Differential Equation Modeling☆53Updated last year
- Code associated with paper "High-Dimensional Contextual Policy Search with Unknown Context Rewards using Bayesian Optimization"☆15Updated 4 years ago
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 6 years ago
- Code repo for "Kernel Interpolation for Scalable Online Gaussian Processes"☆59Updated 4 years ago
- This is a collection of code samples aimed at illustrating temporal parallelization methods for sequential data.☆31Updated last year
- Deep universal probabilistic programming with Python and PyTorch☆11Updated 4 years ago
- Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".☆28Updated last month