rmgarnett / active_gp_hyperlearningLinks
Active learning of GP hyperparameters following Garnett, et al., "Active Learning of Linear Embeddings for Gaussian Processes," (UAI 2014).
☆16Updated 8 years ago
Alternatives and similar repositories for active_gp_hyperlearning
Users that are interested in active_gp_hyperlearning are comparing it to the libraries listed below
Sorting:
- ☆68Updated this week
- Collaborative filtering with the GP-LVM☆25Updated 10 years ago
- The information sieve for discrete variables.☆36Updated 9 years ago
- Stochastic Gradient Riemannian Langevin Dynamics☆34Updated 10 years ago
- Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.☆43Updated 11 years ago
- Variational Fourier Features☆85Updated 4 years ago
- Discriminant Projection Forest results, datasets, etc.☆44Updated 6 years ago
- Python implementation of Markov Jump Hamiltonian Monte Carlo☆24Updated 8 years ago
- scikit-learn addon to operate on set/"group"-based features☆41Updated 9 years ago
- Unsupervised feature learning based on sparse-filtering☆55Updated 11 years ago
- Code for the "Burn CPU, burn" competition at Kaggle. Uses Extreme Learning Machines and hyperopt.☆33Updated 11 years ago
- Rectified Factor Networks☆37Updated 6 years ago
- ☆25Updated 9 years ago
- Fastidious accounting of entropy streams into and out of optimization and sampling algorithms.☆33Updated 9 years ago
- Code for the Kaggle Marinexplore challenge☆17Updated 12 years ago
- Python implementation of nonparametric nearest-neighbor-based estimators for divergences between distributions.☆48Updated 8 years ago
- ☆20Updated 8 years ago
- Sparse Beta-Divergence Tensor Factorization Library☆48Updated 6 months ago
- Document or binary file vectorization with Normalized Compression Distance in Python.☆17Updated 10 years ago
- A simple tool for small scale experiments using bayesian optimization☆35Updated 7 years ago
- ☆18Updated 7 years ago
- my PhD thesis on Bayesian inference☆27Updated 12 years ago
- Implementation of stochastic variational inference for Bayesian hidden Markov models.☆67Updated 8 years ago
- stochs: fast stochastic solvers for machine learning in C++ and Cython☆26Updated 3 years ago
- A library of scalable Bayesian generalised linear models with fancy features☆60Updated 8 years ago
- Sklearn implementation of GBM to predict mu(X) and std(X) on heteroscedastic data☆25Updated 9 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 years ago
- Boosting and ensemble learning in Python.☆54Updated 10 years ago
- Large scale matrix factorization on GPU☆19Updated 9 years ago
- Code for density estimation with nonparametric cluster shapes.☆39Updated 9 years ago