Alternatives and similar repositories for Optimization_and_Sampling_for_Bayesian_Inference:

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

• gianlucadetommaso / Stein-variational-samplers
  Python and MATLAB code for Stein Variational sampling methods
  ☆25Updated 5 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆52Updated 4 years ago
• pmorenoz / ContinualGP
  Continual Gaussian Processes
  ☆32Updated last year
• secondmind-labs / markovflow
  A Tensorflow based library for Time Series Modelling with Gaussian Processes
  ☆30Updated 8 months ago
• Tom-Ryder / VIforSDEs
  A variational method for fast, approximate inference for stochastic differential equations.
  ☆44Updated 6 years ago
• maziarraissi / ParametricGP
  Parametric Gaussian Process Regression for Big Data
  ☆44Updated 5 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• zgbkdlm / ssdgp
  State-space deep Gaussian processes in Python and Matlab
  ☆29Updated 2 years ago
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆46Updated last year
• FelixOpolka / Deep-Gaussian-Process
  🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
  ☆27Updated last year
• cagatayyildiz / npde
  Nonparametric Differential Equation Modeling
  ☆53Updated last year
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆71Updated 4 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆41Updated 8 months ago
• PredictiveIntelligenceLab / GP-NODEs
  ☆29Updated 2 years ago
• RogerFrigola / VGPSSM
  Variational Gaussian Process State-Space Models
  ☆23Updated 9 years ago
• thangbui / sparseGP_powerEP
  Unifying sparse approximations for Gaussian process regression and classification, using Power EP
  ☆22Updated 8 years ago
• sremes / nonstationary-spectral-kernels
  Implementation for Non-stationary Spectral Kernels (NIPS 2017)
  ☆20Updated 5 years ago
• cagatayyildiz / npode
  Learning unknown ODE models with Gaussian processes
  ☆26Updated 6 years ago
• ngorbach / Variational_Gradient_Matching_for_Dynamical_Systems
  Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"
  ☆26Updated 6 years ago
• sorooshafiee / WKF
  ☆14Updated 6 years ago
• maziarraissi / ParametricGP-in-Matlab
  Parametric Gaussian Process Regression for Big Data (Matlab Version)
  ☆24Updated 6 years ago
• pmorenoz / RecyclableGP
  Recyclable Gaussian Processes
  ☆11Updated 2 years ago
• Tom271 / LangevinMC
  MIGSAA Project 2 - Langevin Monte Carlo Algorithms
  ☆12Updated last year
• spbu-math-cs / Riemannian-Gaussian-Processes
  Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".
  ☆28Updated last month
• AaltoML / scalable-inference-in-sdes
  Methods and experiments for assumed density SDE approximations
  ☆11Updated 3 years ago
• anfelopera / lineqGPR
  Gaussian processes regression models with linear inequality constraints
  ☆14Updated 8 months ago
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆65Updated 5 years ago
• erichanslee / GP_Derivatives
  Scalable Gaussian Process Regression with Derivatives
  ☆38Updated 6 years ago
• gatsby-sahani / gp-sde
  ☆14Updated last year
• AaltoML / boundary-gp
  Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features
  ☆23Updated 5 years ago