NicolasDurrande / Gaussian-Processes-short-courseLinks
☆14Updated 8 years ago
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
Sorting:
- R code for ''Bayesian method for causal inference in spatially-correlated multivariate time series''☆46Updated 5 years ago
- Gaussian processes regression models with linear inequality constraints☆15Updated last year
- Source code and data for the tutorial: "Getting started with particle Metropolis-Hastings for inference in nonlinear models"☆28Updated 6 years ago
- Bayesian optimisation for fast approximate inference in state-space models with intractable likelihoods☆13Updated 7 years ago
- Matlab code for my paper "Copula Variational Bayes inference via information geometry", submitted to IEEE Trans. on information theory, 2…☆54Updated 6 years ago
- ☆14Updated 5 years ago
- ☆40Updated 8 years ago
- Empirical comparison of penalized linear regression in high-dimensional settings☆12Updated 5 years ago
- ☆14Updated 6 years ago
- A python tutorial for a Bayesian treatment of Linear Regression: https://zjost.github.io/bayesian-linear-regression/☆82Updated 9 years ago
- Hierarchical Change-Point Detection☆14Updated 6 years ago
- State Space Estimation of Time Series Models in Python: Statsmodels☆44Updated 8 years ago
- Tensorflow implementation of deep quantile regression☆76Updated 3 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆44Updated 7 years ago
- Materials for class on topics in deep learning (STAT 991, UPenn/Wharton)☆95Updated 2 years ago
- A framework to infer causality on a pair of time series of real numbers based on Variable-lag Granger causality and transfer entropy.☆56Updated last year
- ☆21Updated 7 years ago
- Python code for SGMCMC for Time Series SSMs☆13Updated 4 years ago
- Machine Learning vs Statistical Methods for Time Series Forecasting: Size Matters☆41Updated 6 years ago
- Modeling Uncertainty in RNNs for Time Series Forecasting☆15Updated 7 years ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 5 years ago
- Markov Switching Models for Statsmodels☆23Updated 9 years ago
- State-space deep Gaussian processes in Python and Matlab☆30Updated 3 years ago
- Bayesian Dynamic Linear Models for time-series analysis☆27Updated 3 years ago
- Bayesian Gaussian mixture models in Python.☆64Updated 2 years ago
- Applications of Gaussian Process Latent Variable Models in Finance☆11Updated 3 years ago
- Train deepGLM with Matlab, R and Python☆27Updated 2 years ago
- Various packages used by PMTK.☆56Updated 6 years ago
- Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"☆26Updated 6 years ago
- Introductory overview of Bayesian inference☆43Updated 6 years ago