gwgundersen / random-fourier-features
Code for random Fourier features based on Rahimi and Recht's 2007 paper.
☆52Updated 4 years ago
Alternatives and similar repositories for random-fourier-features:
Users that are interested in random-fourier-features are comparing it to the libraries listed below
- Implementation of random Fourier features for kernel method, like support vector machine and Gaussian process model☆100Updated 4 months ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆27Updated 4 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆71Updated 2 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 3 years ago
- Random Fourier Features☆50Updated 7 years ago
- Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for mod…☆118Updated 3 months ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated 9 months ago
- Experiments for Neural Flows paper☆94Updated 3 years ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆169Updated 3 years ago
- ☆101Updated 4 years ago
- Sampling with gradient-based Markov Chain Monte Carlo approaches☆97Updated 11 months ago
- Normalizing Flows with a resampled base distribution☆45Updated 2 years ago
- The Wasserstein Distance and Optimal Transport Map of Gaussian Processes☆52Updated 4 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 5 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆86Updated 2 years ago
- [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)☆117Updated last year
- [AISTATS2020] The official repository of "Invertible Generative Modling using Linear Rational Splines (LRS)".☆20Updated last year
- Light-weighted code for Orthogonal Additive Gaussian Processes☆41Updated 7 months ago
- A library for uncertainty quantification based on PyTorch☆121Updated 3 years ago
- ☆53Updated 7 months ago
- Supplementary code for the AISTATS 2021 paper "Matern Gaussian Processes on Graphs".☆53Updated last month
- Laplace Redux -- Effortless Bayesian Deep Learning☆42Updated last year
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆88Updated 10 months ago
- Regularized Neural ODEs (RNODE)☆82Updated 3 years ago
- PyTorch implementation of the OT-Flow approach in arXiv:2006.00104☆51Updated 7 months ago
- ☆22Updated 4 years ago
- Tutorial materials of the Probabilistic Numerics Spring School.☆34Updated last year
- Learning the optimal transport map via input convex neural neworks☆41Updated 4 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago