Mind-the-Pineapple / sklearn-rvm
An sklearn style implementation of the Relevance Vector Machine (RVM).
☆23Updated 4 years ago
Related projects ⓘ
Alternatives and complementary repositories for sklearn-rvm
- Parametric Gaussian Process Regression for Big Data☆44Updated 4 years ago
- Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen☆25Updated 4 years ago
- Vector Quantile Regression☆19Updated last year
- Contains legacy code and model examples for the paper "BayesFlow: Learning complex stochastic models with invertible neural networks"☆21Updated 3 years ago
- Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"☆18Updated 3 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 3 years ago
- ☆25Updated 6 years ago
- Bayesian Dynamic Mode Decomposition (Bayesian DMD)☆18Updated 2 years ago
- This project provides Slow Feature Analysis as a scikit-learn-style package.☆38Updated last year
- Gaussian process regression + automatical model selection for logitudinal -omics data☆21Updated 3 years ago
- c-lasso: a Python package for constrained sparse regression and classification☆32Updated 3 years ago
- Data-driven modeling of chaotic systems in the form of SDEs and nonlinear observation maps☆17Updated 4 years ago
- Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"☆26Updated 5 years ago
- A Sensitivity and uncertainty analysis toolbox for Python based on the generalized polynomial chaos method☆76Updated 3 weeks ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated 9 months ago
- Implementation of the Gaussian Process Autoregressive Regression Model☆61Updated 3 years ago
- Welcome to Uncertainty Metrics! The goal of this library is to provide an easy-to-use interface for both measuring uncertainty across Goo…☆21Updated 4 years ago
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆28Updated 4 months ago
- Optimal Hard Threshold for Matrix Denoising☆37Updated 3 years ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 4 years ago
- ☆12Updated last year
- Code for: "Neural Controlled Differential Equations for Online Prediction Tasks"☆36Updated 2 years ago
- Python and MATLAB code for Stein Variational sampling methods☆23Updated 5 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆38Updated 3 months ago
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 6 years ago
- Source code of: "Manifold learning-based polynomial chaos expansions for high-dimensional surrogate models".☆37Updated 2 years ago
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆46Updated last year
- Modular Gaussian Processes☆15Updated 2 years ago
- a collection of modern sparse (regularized) linear regression algorithms.☆61Updated 4 years ago
- Pytorch implementation of "Inferring Causal Dependencies between Chaotic Dynamical Systems from Sporadic Time Series"☆9Updated 4 years ago