davharris / mcmc-tutorialLinks
Tutorial introducing Monte Carlo integration and Markov Chain Monte Carlo
☆52Updated 12 years ago
Alternatives and similar repositories for mcmc-tutorial
Users that are interested in mcmc-tutorial are comparing it to the libraries listed below
Sorting:
- Large Scale Machine learning Optimization through Stochastic Average Gradient☆9Updated 9 years ago
- Mirror of Apache Spark☆24Updated 9 years ago
- Image Classification using MXNetR☆55Updated 8 years ago
- National Data Science Bowl☆20Updated 10 years ago
- Code and text for our NIPS 2015 paper on linear response variational Bayes☆19Updated 7 years ago
- Using stochastic gradient descent (SGD) with explicit and implicit updates to fit large-scale statistical models.☆16Updated 10 years ago
- Fast, principled L1-regularized loss minimization☆24Updated last year
- Software for learning sparse Bayesian networks☆43Updated 4 years ago
- A C++ package for discrete distribution based large-scale data processing framework☆2Updated 7 years ago
- LDA in Python.☆26Updated 11 years ago
- Advanced workshop on XGBoost with Tianqi Chen in Santa Monica, June 2, 2016☆26Updated 8 years ago
- An R package for large scale estimation with stochastic gradient descent☆62Updated last year
- A parallel IRWLS library to solve SVMs and budgeted SVMs☆59Updated 7 years ago
- ☆44Updated 10 years ago
- ☆32Updated 5 years ago
- Notebooks containing R code from Richard McElreath's Statistical Rethinking☆72Updated 9 years ago
- Course materials for STA663☆37Updated 9 years ago
- Discriminant Projection Forest results, datasets, etc.☆44Updated 5 years ago
- Bayesian Poisson Tucker decomposition☆17Updated 8 years ago
- An implementation of the Hessian-free optimization algorithm in Theano☆61Updated 13 years ago
- Module 7: Introduction to D3.js☆21Updated 9 years ago
- Online Multi-Class LPBoost and Gradient Boosting☆68Updated 10 years ago
- The pdf and LaTeX for each paper (and sometimes the code and data used to generate the figures).☆72Updated 8 years ago
- Implementation of stochastic variational inference for Bayesian hidden Markov models.☆69Updated 7 years ago
- Benchmarking different LSTM libraries☆24Updated 9 years ago
- Python package for inference with Gaussian processes☆11Updated 10 years ago
- ADMM on Apache Spark☆31Updated 10 years ago
- Bayesian dessert for Lasagne☆83Updated 8 years ago
- Deep learning made easy☆116Updated 11 years ago
- ☆24Updated 9 years ago