Alternatives and similar repositories for random-fourier-features:

Users that are interested in random-fourier-features are comparing it to the libraries listed below

• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 4 years ago
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 5 years ago
• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆87Updated 2 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆83Updated 9 months ago
• alisiahkoohi / Langevin-dynamics
  Sampling with gradient-based Markov Chain Monte Carlo approaches
  ☆97Updated 11 months ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆57Updated 3 years ago
• tiskw / random-fourier-features
  Implementation of random Fourier features for kernel method, like support vector machine and Gaussian process model
  ☆100Updated 5 months ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆72Updated 2 years ago
• spbu-math-cs / Graph-Gaussian-Processes
  Supplementary code for the AISTATS 2021 paper "Matern Gaussian Processes on Graphs".
  ☆53Updated last month
• VincentStimper / resampled-base-flows
  Normalizing Flows with a resampled base distribution
  ☆46Updated 2 years ago
• hichamjanati / srf
  Random Fourier Features
  ☆50Updated 7 years ago
• facebookresearch / w2ot
  Euclidean Wasserstein-2 optimal transportation
  ☆46Updated last year
• federicobergamin / riemannian-laplace-approximation
  Repository for the paper "Riemannian Laplace approximations for Bayesian neural networks"
  ☆11Updated last year
• AmirTag / OT-ICNN
  Learning the optimal transport map via input convex neural neworks
  ☆41Updated 4 years ago
• dtak / ocbnn-public
  General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.
  ☆38Updated 2 years ago
• cambridge-mlg / cnn-gp
  Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…
  ☆32Updated 4 years ago
• mbilos / neural-flows-experiments
  Experiments for Neural Flows paper
  ☆94Updated 3 years ago
• f-dangel / phd-thesis
  Source code for my PhD thesis: Backpropagation Beyond the Gradient
  ☆20Updated 2 years ago
• chenlin9 / Gaussianization_Flows
  ☆22Updated 4 years ago
• hmdolatabadi / LRS_NF
  [AISTATS2020] The official repository of "Invertible Generative Modling using Linear Rational Splines (LRS)".
  ☆20Updated last year
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆47Updated last year
• ehoogeboom / convolution_exponential_and_sylvester
  ☆28Updated 3 years ago
• massastrello / awesome-implicit-neural-models
  ☆101Updated 4 years ago
• MichaelArbel / GeneralizedEBM
  ☆53Updated 8 months ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆41Updated 8 months ago
• AWehenkel / UMNN
  Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for mod…
  ☆118Updated 3 months ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆31Updated 4 years ago
• probabilistic-numerics / probnum-spring-school
  Tutorial materials of the Probabilistic Numerics Spring School.
  ☆34Updated last year
• CUAI / Neural-Manifold-Ordinary-Differential-Equations
  [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)
  ☆117Updated last year
• f-dangel / curvlinops
  PyTorch linear operators for curvature matrices (Hessian, Fisher/GGN, KFAC, ...)
  ☆34Updated 3 weeks ago