jungtaekkim / bayeso-benchmarksLinks
Benchmark functions for Bayesian optimization
☆33Updated last year
Alternatives and similar repositories for bayeso-benchmarks
Users that are interested in bayeso-benchmarks are comparing it to the libraries listed below
Sorting:
- Code for A General Recipe for Likelihood-free Bayesian Optimization, ICML 2022☆44Updated 2 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- ☆51Updated 11 months ago
- Re-Examining Linear Embeddings for High-dimensional Bayesian Optimization☆41Updated 3 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Limitations of the Empirical Fisher Approximation☆47Updated 3 months ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆85Updated 4 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆32Updated 3 years ago
- Implementation of the Functional Neural Process models☆43Updated 4 years ago
- The High-dimensional BayesOpt algorithms from "A Framework for Bayesian Optimization in Embedded Subspaces☆41Updated 6 years ago
- Simple, but essential Bayesian optimization package☆94Updated 5 months ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 3 years ago
- Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design☆34Updated 4 years ago
- Bayesian Optimisation over Multiple Continuous and Categorical Inputs (CoCaBO)☆51Updated 5 years ago
- Baselines for Model-Based Optimization☆53Updated 3 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated last year
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆19Updated 3 years ago
- ☆16Updated 6 years ago
- Pytorch implementation for "Particle Flow Bayes' Rule"☆14Updated 6 years ago
- ☆54Updated 11 months ago
- Pytorch implementation of neural processes and variants☆29Updated 11 months ago
- Code repository for Ensemble Bayesian Optimization☆53Updated 5 years ago
- Code for "On the Expressiveness of Approximate Inference in Bayesian Neural Networks"☆13Updated 3 years ago
- Natural Gradient, Variational Inference☆29Updated 5 years ago
- Parallelised Thompson Sampling in GPs for Bayesian Optimisation☆36Updated 7 years ago
- Code for Knowledge-Adaptation Priors based on the NeurIPS 2021 paper by Khan and Swaroop.☆16Updated 3 years ago
- ☆67Updated 6 years ago
- A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"☆21Updated 6 years ago