Alternatives and similar repositories for kitt:

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

• pmorenoz / ModularGP
  Modular Gaussian Processes
  ☆15Updated 3 years ago
• hegdepashupati / differential-dgp
  Implementation of stochastic variational inference for differentially deep gaussian processes
  ☆15Updated 6 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆42Updated 9 months ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆19Updated 3 years ago
• google-deepmind / annealed_flow_transport
  ☆52Updated 2 years ago
• PrincetonLIPS / AHGP
  [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)
  ☆21Updated 4 years ago
• crispitagorico / sigkernel
  Differentiable computations for the signature-PDE-kernel on CPU and GPU.
  ☆54Updated 11 months ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆31Updated 4 years ago
• BorealisAI / continuous-time-flow-process
  PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)
  ☆48Updated 4 years ago
• LaurenceA / bayesfunc
  ☆15Updated 2 years ago
• jeremiecoullon / SGMCMCJax
  Lightweight library of stochastic gradient MCMC algorithms written in JAX.
  ☆103Updated last year
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• JTT94 / filterflow
  Extensible Tensorflow library for differentiable particle filtering. ICML 2021.
  ☆42Updated 2 years ago
• andrew-cr / online_var_fil
  Code for our paper: Online Variational Filtering and Parameter Learning
  ☆18Updated 3 years ago
• runame / laplace-refinement
  Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks
  ☆10Updated 2 years ago
• markvdw / RobustGP
  Robust initialisation of inducing points in sparse variational GP regression models.
  ☆33Updated 2 years ago
• conormdurkan / lfi
  Neural likelihood-free methods in PyTorch.
  ☆39Updated 5 years ago
• aterenin / SparseGPAX
  An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.
  ☆22Updated 4 years ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆72Updated 4 years ago
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 6 years ago
• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆125Updated 6 months ago
• ialong / GPt
  Gaussian Processes for Sequential Data
  ☆18Updated 4 years ago
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆24Updated 2 years ago
• jamesvuc / jax-bayes
  Bayesian inference with Python and Jax.
  ☆32Updated 2 years ago
• secondmind-labs / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆11Updated last year
• ratschlab / repulsive_ensembles
  Repo for our paper "Repulsive deep ensembles are Bayesian"
  ☆19Updated 3 years ago
• secondmind-labs / markovflow
  A Tensorflow based library for Time Series Modelling with Gaussian Processes
  ☆30Updated 10 months ago
• AVMCMC / AuxiliaryVariationalMCMC
  Code required to reproduce the experiments in Auxiliary Variational MCMC
  ☆17Updated 6 years ago
• AaltoML / scalable-inference-in-sdes
  Methods and experiments for assumed density SDE approximations
  ☆12Updated 3 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆72Updated 3 years ago