Alternatives and similar repositories for Gaussian-Processes-short-course:

Users that are interested in Gaussian-Processes-short-course are comparing it to the libraries listed below

• alan-turing-institute / rbocpdms
  Robust bayesian online changepoint detection with model selection
  ☆23Updated 6 years ago
• anfelopera / lineqGPR
  Gaussian processes regression models with linear inequality constraints
  ☆14Updated 8 months ago
• thiery-lab / manifold-mcmc-for-diffusions
  Code accompanying the paper 'Manifold MCMC methods for Bayesian inference in a wide class of diffusion models'
  ☆10Updated last year
• PhIMaL / DeePyMoD_tensorflow
  This implementation of DeePyMoD is no longer maintained! We switched to a PyTorch based implementation: https://github.com/PhIMaL/DeePyM…
  ☆24Updated 5 years ago
• compops / gpo-smc-abc
  Bayesian optimisation for fast approximate inference in state-space models with intractable likelihoods
  ☆12Updated 7 years ago
• chaaland / bloomberg-ml-course
  Solutions to machine learning HW from bloomberg ml course
  ☆11Updated 5 years ago
• VBayesLab / VBLab
  Official documentation
  ☆28Updated 4 years ago
• ChadFulton / fulton_statsmodels_2017
  State Space Estimation of Time Series Models in Python: Statsmodels
  ☆43Updated 8 years ago
• caisr-hh / group-anomaly-detection
  GRAND: Group-based Anomaly Detection for Large-Scale Monitoring of Complex Systems
  ☆15Updated 4 years ago
• AaltoML / boundary-gp
  Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features
  ☆23Updated 5 years ago
• compops / pmh-tutorial
  Source code and data for the tutorial: "Getting started with particle Metropolis-Hastings for inference in nonlinear models"
  ☆28Updated 5 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
• ChadFulton / pymar
  Markov Switching Models for Statsmodels
  ☆22Updated 8 years ago
• deepcharles / tutorials-mva-2022
  Tutorials for the Machine Learning for Time Series class - Master MVA (2021/2022)
  ☆10Updated 3 years ago
• paulorauber / pgm
  Probabilistic graphical models in python
  ☆23Updated 6 years ago
• roboticcam / DLS_meetup_2018_02
  Contains all presentations for Deep Learning Sydney Meetup 2018 02
  ☆18Updated 7 years ago
• convexfi / fitHeavyTail
  Mean and Covariance Matrix Estimation under Heavy Tails
  ☆22Updated last year
• rsnirwan / GPLVMsInFinance
  Applications of Gaussian Process Latent Variable Models in Finance
  ☆11Updated 2 years ago
• NicolasDurrande / Gaussian-Process-Regression-handout
  ☆38Updated 8 years ago
• vcerqueira / MLforForecasting
  Machine Learning vs Statistical Methods for Time Series Forecasting: Size Matters
  ☆40Updated 5 years ago
• Tom-Ryder / VIforSDEs
  A variational method for fast, approximate inference for stochastic differential equations.
  ☆44Updated 6 years ago
• tminka / fastfit
  Fastfit matlab toolbox
  ☆27Updated 8 years ago
• chlubba / op_importance
  Compute set of important operations for HCTSA code
  ☆26Updated 4 years ago
• AaltoML / IHGP
  Infinite-horizon Gaussian processes
  ☆32Updated 4 years ago
• philipk01 / Optimization_and_Sampling_for_Bayesian_Inference
  Adaptive MCMC and CMA-ES Python code
  ☆14Updated 5 years ago
• fw307 / high_dimensional_regression_comparison
  Empirical comparison of penalized linear regression in high-dimensional settings
  ☆12Updated 5 years ago
• VietTran86 / Copula-Variational-Bayes
  Matlab code for my paper "Copula Variational Bayes inference via information geometry", submitted to IEEE Trans. on information theory, 2…
  ☆52Updated 6 years ago
• duke-mlss / Duke-MLWS-2019
  Duke Machine Learning Winter School 2019
  ☆27Updated 6 years ago
• christinaheinze / causality-course-ethz
  Code used in the causality course (401-4632-15) at ETH Zurich.
  ☆22Updated 5 years ago
• PredictiveIntelligenceLab / JAX-BO
  ☆30Updated 2 years ago