Alternatives and similar repositories for kitt

Users that are interested in kitt are comparing it to the libraries listed below

• PrincetonLIPS / AHGP
  [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)
  ☆22Updated 4 years ago
• runame / laplace-refinement
  Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks
  ☆10Updated 2 years ago
• pmorenoz / ModularGP
  Modular Gaussian Processes
  ☆15Updated 3 years ago
• google-deepmind / annealed_flow_transport
  ☆52Updated 2 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆43Updated last year
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆20Updated 3 years ago
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 6 years ago
• jeremiecoullon / SGMCMCJax
  Lightweight library of stochastic gradient MCMC algorithms written in JAX.
  ☆104Updated last year
• dngfra / repulsive_ensembles
  Repo for our paper "Repulsive deep ensembles are Bayesian"
  ☆19Updated 3 years ago
• wesselb / neuralprocesses
  A framework for composing Neural Processes in Python
  ☆85Updated 8 months ago
• PetrMokrov / Large-Scale-Wasserstein-Gradient-Flows
  Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)
  ☆35Updated 3 years ago
• DanieleGammelli / pyro-torch-normalizing-flows
  Implementations of Normalizing Flows in Pytorch/Pyro
  ☆19Updated 5 years ago
• secondmind-labs / markovflow
  A Tensorflow based library for Time Series Modelling with Gaussian Processes
  ☆32Updated last year
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆74Updated 3 years ago
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆24Updated 2 years ago
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆42Updated 2 months ago
• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆127Updated 10 months ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆73Updated 4 years ago
• VincentStimper / resampled-base-flows
  Normalizing Flows with a resampled base distribution
  ☆47Updated 2 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆32Updated 4 years ago
• LaurenceA / bayesfunc
  ☆15Updated 2 years ago
• conormdurkan / lfi
  Neural likelihood-free methods in PyTorch.
  ☆39Updated 5 years ago
• joneswack / dp-rfs
  This repository contains PyTorch implementations of various random feature maps for dot product kernels.
  ☆21Updated last year
• hegdepashupati / differential-dgp
  Implementation of stochastic variational inference for differentially deep gaussian processes
  ☆15Updated 6 years ago
• Benjamin-Walker / log-neural-cdes
  Code for "Log Neural Controlled Differential Equations: The Lie Brackets Make a Difference" (ICML 2024)
  ☆22Updated 3 months ago
• crispitagorico / sigkernel
  Differentiable computations for the signature-PDE-kernel on CPU and GPU.
  ☆56Updated last year
• andrew-cr / online_var_fil
  Code for our paper: Online Variational Filtering and Parameter Learning
  ☆18Updated 3 years ago
• BorealisAI / continuous-time-flow-process
  PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)
  ☆48Updated 4 years ago
• JTT94 / filterflow
  Extensible Tensorflow library for differentiable particle filtering. ICML 2021.
  ☆42Updated 2 years ago
• federicobergamin / riemannian-laplace-approximation
  Repository for the paper "Riemannian Laplace approximations for Bayesian neural networks"
  ☆11Updated last year