Alternatives and similar repositories for VIforSDEs

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

• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 7 years ago
• AaltoML / boundary-gp
  Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features
  ☆24Updated 6 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆32Updated 5 years ago
• gianlucadetommaso / Stein-variational-samplers
  Python and MATLAB code for Stein Variational sampling methods
  ☆27Updated 6 years ago
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆65Updated 6 years ago
• sremes / nonstationary-spectral-kernels
  Implementation for Non-stationary Spectral Kernels (NIPS 2017)
  ☆20Updated 6 years ago
• gpapamak / snl
  Sequential Neural Likelihood
  ☆42Updated 6 years ago
• pierresegonne / VINF
  Repository for DTU Special Course, focusing on Variational Inference using Normalizing Flows (VINF). Supervised by Michael Riis Andersen
  ☆26Updated 5 years ago
• cagatayyildiz / npde
  Nonparametric Differential Equation Modeling
  ☆56Updated last year
• idelbrid / Randomly-Projected-Additive-GPs
  Code for Randomly Projected Additive Gaussian Processes
  ☆25Updated 6 years ago
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆69Updated last year
• PredictiveIntelligenceLab / JAX-BO
  ☆30Updated 3 years ago
• yorkerlin / VB-MixEF
  Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"
  ☆19Updated 5 years ago
• robert-giaquinto / gradient-boosted-normalizing-flows
  We got a stew going!
  ☆27Updated 2 years ago
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 4 years ago
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆50Updated 2 years ago
• patrick-kidger / Deep-Signature-Transforms
  Code for "Deep Signature Transforms" (NeurIPS 2019)
  ☆98Updated last year
• BorealisAI / continuous-time-flow-process
  PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)
  ☆47Updated 5 years ago
• secondmind-labs / markovflow
  A Tensorflow based library for Time Series Modelling with Gaussian Processes
  ☆32Updated last year
• aterenin / SparseGPAX
  An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.
  ☆22Updated 4 years ago
• hegdepashupati / differential-dgp
  Implementation of stochastic variational inference for differentially deep gaussian processes
  ☆15Updated 7 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆83Updated last year
• lxuechen / BDMC
  PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.
  ☆52Updated 4 years ago
• microsoft / vi-hds
  Variational inference for hierarchical dynamical systems
  ☆50Updated last year
• ngorbach / Variational_Gradient_Matching_for_Dynamical_Systems
  Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"
  ☆26Updated 6 years ago
• cambridge-mlg / sghmc_dgp
  ☆29Updated 6 years ago
• AaltoML / hilbert-gp
  Codes for Hilbert space reduced-rank GP regression
  ☆14Updated 6 years ago
• mattja / nsim
  Large scale simulation of ODEs or SDEs, analyze time series.
  ☆25Updated 6 years ago
• gatsby-sahani / gp-sde
  ☆15Updated 2 years ago
• LaurenceA / bayesfunc
  ☆15Updated 3 years ago