google-research / hyperboLinks
Pre-trained Gaussian processes for Bayesian optimization
☆91Updated last month
Alternatives and similar repositories for hyperbo
Users that are interested in hyperbo are comparing it to the libraries listed below
Sorting:
- ☆30Updated 8 months ago
- Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization☆72Updated 2 years ago
- Bayesian Neural Network Surrogates for Bayesian Optimization☆51Updated last year
- The official implementation of PFNs4BO: In-Context Learning for Bayesian Optimization☆28Updated last year
- Bayesian Optimization with Density-Ratio Estimation☆23Updated 2 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆72Updated 4 years ago
- Multi-Objective Bayesian Optimization over High-Dimensional Search Spaces☆57Updated 2 years ago
- Code for A General Recipe for Likelihood-free Bayesian Optimization, ICML 2022☆44Updated 2 years ago
- Bayesian algorithm execution (BAX)☆49Updated 3 years ago
- SAASBO: a package for high-dimensional bayesian optimization☆43Updated 3 years ago
- [ICML'21] Think Global and Act Local: Bayesian Optimisation for Categorical and Mixed Search Spaces☆30Updated 2 years ago
- Bayesian optimization of discrete sequences☆21Updated 3 years ago
- Bayesian inference with Python and Jax.☆32Updated 2 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆42Updated 2 years ago
- ☆15Updated 2 years ago
- Code for "A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences"☆11Updated 3 months ago
- Re-Examining Linear Embeddings for High-dimensional Bayesian Optimization☆41Updated 3 years ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆125Updated 7 months ago
- This is the code for our paper: Increasing the Scope as You Learn: Adaptive Bayesian Optimization in Nested Subspaces (Leonard Papenmeier…☆17Updated last year
- A Bayesian optimization toolbox built on TensorFlow☆234Updated last week
- Benchmark functions for Bayesian optimization☆33Updated last year
- ☆79Updated last month
- [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)☆21Updated 4 years ago
- Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design☆32Updated 3 years ago
- ☆114Updated this week
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆19Updated 3 years ago
- Python implementation for Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces.☆13Updated 3 years ago
- Riemannian Optimization Using JAX☆49Updated last year
- Simple (and cheap!) neural network uncertainty estimation☆66Updated last week
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆103Updated last year