Alternatives and similar repositories for DeepStructuredMixtures

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

• cagatayyildiz / npde
  Nonparametric Differential Equation Modeling
  ☆56Updated last year
• ialong / GPt
  Gaussian Processes for Sequential Data
  ☆18Updated 4 years ago
• pmorenoz / ContinualGP
  Continual Gaussian Processes
  ☆31Updated 2 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• thangbui / sparseGP_powerEP
  Unifying sparse approximations for Gaussian process regression and classification, using Power EP
  ☆22Updated 9 years ago
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆73Updated 5 years ago
• wesselb / NeuralProcesses.jl
  A framework for composing Neural Processes in Julia
  ☆76Updated 4 years ago
• secondmind-labs / markovflow
  A Tensorflow based library for Time Series Modelling with Gaussian Processes
  ☆32Updated last year
• sremes / nonstationary-spectral-kernels
  Implementation for Non-stationary Spectral Kernels (NIPS 2017)
  ☆20Updated 5 years ago
• ntienvu / KnownOptimum_BO
  Release code for ICML2020 Knowing The What But Not The Where in Bayesian Optimization
  ☆15Updated 2 years ago
• thangbui / streaming_sparse_gp
  Streaming sparse Gaussian process approximations
  ☆68Updated 3 years ago
• gatsby-sahani / gp-sde
  ☆15Updated 2 years ago
• aterenin / SparseGaussianProcesses.jl
  A Julia implementation of sparse Gaussian processes via path-wise doubly stochastic variational inference.
  ☆33Updated 5 years ago
• wjmaddox / online_gp
  Code repo for "Kernel Interpolation for Scalable Online Gaussian Processes"
  ☆64Updated 4 years ago
• markvdw / RobustGP
  Robust initialisation of inducing points in sparse variational GP regression models.
  ☆33Updated 3 years ago
• f-dangel / phd-thesis
  Source code for my PhD thesis: Backpropagation Beyond the Gradient
  ☆20Updated 2 years ago
• AaltoML / hilbert-gp
  Codes for Hilbert space reduced-rank GP regression
  ☆14Updated 6 years ago
• cagatayyildiz / npode
  Learning unknown ODE models with Gaussian processes
  ☆27Updated 7 years ago
• gianlucadetommaso / Stein-variational-samplers
  Python and MATLAB code for Stein Variational sampling methods
  ☆26Updated 6 years ago
• plugyawn / gp-zoo
  A repository with implementations of major papers on Gaussian Process regression models, implemented from scratch in Python, notably incl…
  ☆14Updated 3 years ago
• paulxshen / neural-ode-cartpole
  ☆24Updated 5 years ago
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 6 years ago
• QB3 / sparse-ho
  Fast hyperparameter settings for non-smooth estimators:
  ☆40Updated 2 years ago
• AaltoML / boundary-gp
  Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features
  ☆24Updated 6 years ago
• hughsalimbeni / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆112Updated 4 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆54Updated 5 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
• erichanslee / GP_Derivatives
  Scalable Gaussian Process Regression with Derivatives
  ☆38Updated 6 years ago
• RajDandekar / MSML21_BayesianNODE
  ☆40Updated 4 years ago
• vienmai / drot
  Douglas-Rachford Splitting for Optimal Transport
  ☆11Updated 4 years ago