QUVA-Lab / COMBOLinks
☆50Updated last year
Alternatives and similar repositories for COMBO
Users that are interested in COMBO are comparing it to the libraries listed below
Sorting:
- Code repository for Ensemble Bayesian Optimization☆57Updated 6 years ago
- Bayesian Optimisation over Multiple Continuous and Categorical Inputs (CoCaBO)☆52Updated 6 years ago
- Re-Examining Linear Embeddings for High-dimensional Bayesian Optimization☆42Updated 4 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 5 years ago
- Bayesian Optimization over Discrete and Mixed Spaces via Probabilistic Reparameterization☆76Updated 3 years ago
- The High-dimensional BayesOpt algorithms from "A Framework for Bayesian Optimization in Embedded Subspaces☆43Updated 6 years ago
- Parallelised Thompson Sampling in GPs for Bayesian Optimisation☆36Updated 8 years ago
- Benchmark functions for Bayesian optimization☆37Updated last year
- Bayesian neural network package☆155Updated 4 years ago
- gpbo☆25Updated 5 years ago
- Code for the paper "Learning Step-Size Adaptation in CMA-ES"☆12Updated 2 years ago
- Bayesian algorithm execution (BAX)☆55Updated 4 years ago
- ☆17Updated 7 years ago
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 4 years ago
- ☆23Updated 3 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 7 years ago
- [ICML'21] Think Global and Act Local: Bayesian Optimisation for Categorical and Mixed Search Spaces☆33Updated 3 years ago
- CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.☆78Updated last year
- ☆26Updated 7 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 6 years ago
- ☆172Updated last year
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- Implementation of random Fourier features for kernel method, like support vector machine and Gaussian process model☆103Updated last year
- Bayesian optimization in high-dimensions via random embedding.☆116Updated 12 years ago
- ☆59Updated 6 years ago
- Scalable Log Determinants for Gaussian Process Kernel Learning (https://arxiv.org/abs/1711.03481) (NIPS 2017)☆18Updated 8 years ago
- ☆30Updated 3 years ago
- Neural Processes implementation for 1D regression☆64Updated 6 years ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆36Updated 4 years ago
- Sparse Orthogonal Variational Inference for Gaussian Processes (SOLVE-GP)☆22Updated 4 years ago