nkantas / LTCC-Advanced-Computational-Methods-in-Statistics
Advanced LTCC course in StatisticsThis course will provide an overview of Monte Carlo methods when used for problems in Statistics. After an introduction to simulation, its purpose and challenges, we will cover in more detail Importance Sampling, Markov Chain Monte Carlo and Sequential Monte Carlo. Whilst the main focus will be on the methodolog…
☆26Updated 2 years ago
Alternatives and similar repositories for LTCC-Advanced-Computational-Methods-in-Statistics:
Users that are interested in LTCC-Advanced-Computational-Methods-in-Statistics are comparing it to the libraries listed below
- Tutorials and sampling algorithm comparisons☆72Updated this week
- some scripts for the couplings enthusiasts!☆32Updated 4 years ago
- Self-tuning HMC algorithms and evaluations☆18Updated 5 months ago
- Structural Time Series in JAX☆188Updated 10 months ago
- Course material for the PhD course in Advanced Bayesian Learning☆59Updated last month
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆102Updated last year
- ☆21Updated 6 months ago
- State of the art inference for your bayesian models.☆204Updated 3 months ago
- Official Github for Wharton STAT 4830☆26Updated this week
- AeMCMC is a Python library that automates the construction of samplers for Aesara graphs representing statistical models.☆39Updated last year
- A simple library to run variational inference on Stan models.☆30Updated last year
- Neat Bayesian machine learning examples☆55Updated 2 months ago
- Bayesian inference and posterior analysis for Python☆44Updated last year
- Recursive Bayesian Estimation (Sequential / Online Inference)☆58Updated 11 months ago
- Computational Statistics and Statistical Computing☆37Updated 3 years ago
- Following along with Statistical Rethinking text on Bayesian modeling by McElreath☆59Updated 4 years ago
- Notes for the Numerics of Machine Learning Lecture Course at the University of Tübingen☆198Updated last year
- ☆152Updated 3 weeks ago
- A generic library for linear and non-linear Gaussian smoothing problems. The code leverages JAX and implements several linearization algo…☆12Updated 3 months ago
- The code in this repository follows the paper "Stochastic gradient MCMC"☆26Updated 5 years ago
- Black-Box Inference foR Differentiable Simulators☆17Updated 4 months ago
- Public code for running Stochastic Gradient Descent on GPs.☆36Updated 5 months ago
- Tutorial materials of the Probabilistic Numerics Spring School.☆34Updated last year
- Lectures on Quantitative Economics Using JAX☆36Updated last week
- Lecture "A computational introduction to stochastic differential equations".☆18Updated 2 years ago
- Powerful add-ons for PyMC☆98Updated last week
- Materials and syllabus for Cornell ORIE 7391, Faster: Algorithmic Ideas for Speeding Up Optimization☆23Updated 2 years ago
- A light interface to serial and multi-threaded Sequential Monte Carlo☆31Updated 3 years ago
- Source code related to the article "Deep splitting method for parabolic PDEs" by Christian Beck, Sebastian Becker, Patrick Cheridito, Arn…☆14Updated 4 years ago
- Probabilistic solvers for differential equations in JAX. Adaptive ODE solvers with calibration, state-space model factorisations, and cus…☆44Updated this week