fredhallgren / nystrompca
Efficient non-linear PCA through kernel PCA with the Nyström method
☆13Updated last year
Alternatives and similar repositories for nystrompca:
Users that are interested in nystrompca are comparing it to the libraries listed below
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 6 years ago
- Modular Gaussian Processes☆15Updated 3 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 5 years ago
- Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods☆22Updated last year
- Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"☆18Updated 4 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 6 years ago
- Recyclable Gaussian Processes☆11Updated 2 years ago
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 4 years ago
- Code for the paper "Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations"☆28Updated 5 months ago
- Contains legacy code and model examples for the paper "BayesFlow: Learning complex stochastic models with invertible neural networks"☆22Updated 4 years ago
- ☆14Updated last year
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆47Updated last year
- ☆30Updated 2 years ago
- Code required to reproduce the experiments in Auxiliary Variational MCMC☆17Updated 6 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆41Updated 8 months ago
- Code for NeurIPS 2021 paper 'Spatio-Temporal Variational Gaussian Processes'☆47Updated 3 years ago
- Implementations of various random kitchen sinks algorithms.☆12Updated 5 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆27Updated last year
- Material for the practical of the DS3 course on "Representing and comparing probabilities with kernels"☆26Updated 6 years ago
- Codes for Hilbert space reduced-rank GP regression☆14Updated 5 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆38Updated 5 years ago
- Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features☆23Updated 5 years ago
- Bayesian and Maximum Likelihood Implementation of the Normalizing Flow Network (NFN): https://arxiv.org/abs/1907.08982☆21Updated 4 years ago
- A library implementing the kernels for and experiments using extrinsic gauge equivariant vector field Gaussian Processes☆25Updated 3 years ago
- Python and MATLAB code for Stein Variational sampling methods☆25Updated 5 years ago
- Methods and experiments for assumed density SDE approximations☆11Updated 3 years ago
- Bayesian optimization with conformal coverage guarantees☆27Updated 2 years ago
- Kernel Identification Through Transformers☆12Updated last year