tiskw / random-fourier-featuresLinks
Implementation of random Fourier features for kernel method, like support vector machine and Gaussian process model
☆103Updated last year
Alternatives and similar repositories for random-fourier-features
Users that are interested in random-fourier-features are comparing it to the libraries listed below
Sorting:
- ☆155Updated 3 years ago
- Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances☆50Updated 2 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 7 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 4 years ago
- Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for mod…☆125Updated 3 weeks ago
- Code for random Fourier features based on Rahimi and Recht's 2007 paper.☆58Updated 5 years ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 5 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆25Updated last year
- Light-weighted code for Orthogonal Additive Gaussian Processes☆43Updated last year
- Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.☆63Updated 4 years ago
- Heterogeneous Multi-output Gaussian Processes☆54Updated 5 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆90Updated 5 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆75Updated 3 years ago
- Bayesian Deep Learning with Stochastic Gradient MCMC Methods☆38Updated 4 years ago
- Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.☆227Updated last year
- A community repository for benchmarking Bayesian methods☆112Updated 4 years ago
- code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"☆100Updated 6 years ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆25Updated 3 years ago
- PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)☆47Updated 5 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- Code for efficiently sampling functions from GP(flow) posteriors☆74Updated 5 years ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆171Updated 3 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- Continual Gaussian Processes☆31Updated 2 years ago
- Bayesian Neural Network Surrogates for Bayesian Optimization☆65Updated last year
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 6 years ago
- Robust initialisation of inducing points in sparse variational GP regression models.☆34Updated 3 years ago
- Sequential Neural Likelihood☆42Updated 6 years ago