mwhoffman / pyboLinks
Python package for modular Bayesian optimization
☆136Updated 5 years ago
Alternatives and similar repositories for pybo
Users that are interested in pybo are comparing it to the libraries listed below
Sorting:
- HPOlib is a hyperparameter optimization library. It provides a common interface to three state of the art hyperparameter optimization pac…☆166Updated 7 years ago
- Optimizers for machine learning☆183Updated 2 years ago
- Exploring differentiation with respect to hyperparameters☆296Updated 10 years ago
- Implementation in C and Theano of the method Probabilistic Backpropagation for scalable Bayesian inference in deep neural networks.☆191Updated 6 years ago
- Bayesian dessert for Lasagne☆83Updated 8 years ago
- Flexible Bayesian inference using TensorFlow☆142Updated 8 years ago
- Implements SFO minibatch optimizer in Python and MATLAB, and reproduces figures from paper.☆132Updated 4 years ago
- Kernel structure discovery research code - likely to be unstable☆195Updated 10 years ago
- ☆99Updated 7 years ago
- Variational and semi-supervised neural network toppings for Lasagne☆210Updated 9 years ago
- Collection of jupyter notebooks for demonstrating software.☆169Updated 2 years ago
- Deep exponential families (DEFs)☆55Updated 7 years ago
- Stochastic gradient routines for Theano☆103Updated 7 years ago
- Deep GPs with GPy☆31Updated 9 years ago
- Code for Mondrian Forests (for classification and regression)☆268Updated 9 years ago
- A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation☆128Updated 4 years ago
- Collaborative filtering with the GP-LVM☆25Updated 10 years ago
- A Gaussian process toolbox in python☆42Updated 13 years ago
- Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.☆251Updated last year
- Bayesian Optimization using GPflow☆272Updated 5 years ago
- ☆25Updated 3 years ago
- 1st place submission to the AutoML competition - phase 2☆28Updated 10 years ago
- megaman: Manifold Learning for Millions of Points☆333Updated 2 years ago
- Backpropagate derivatives through the Cholesky decomposition☆59Updated 5 years ago
- Spearmint, without the gum☆42Updated 8 years ago
- Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.☆44Updated 11 years ago
- We use a modified neural network instead of Gaussian process for Bayesian optimization.☆108Updated 8 years ago
- Randomized online matrix factorization☆139Updated 5 years ago
- Bayesian Logistic Regression using Laplace approximations to the posterior.☆48Updated 8 years ago
- Fastidious accounting of entropy streams into and out of optimization and sampling algorithms.☆33Updated 9 years ago