davharris / mcmc-tutorial
Tutorial introducing Monte Carlo integration and Markov Chain Monte Carlo
☆51Updated 11 years ago
Related projects: ⓘ
- Large Scale Machine learning Optimization through Stochastic Average Gradient☆9Updated 8 years ago
- The programming assignments from CS228T offered in Spring 2012 at Stanford☆40Updated 11 years ago
- Using stochastic gradient descent (SGD) with explicit and implicit updates to fit large-scale statistical models.☆16Updated 10 years ago
- LDA in Python.☆25Updated 10 years ago
- Mirror of Apache Spark☆24Updated 8 years ago
- Image Classification using MXNetR☆56Updated 7 years ago
- Wrappers of Jerome Friedman's coordinate-descent Fortran implementation of lasso/elastic net regression from the R "glmnet" package.☆35Updated 14 years ago
- ☆55Updated this week
- A comparative study of different LSTM structures☆33Updated 8 years ago
- A C++ package for discrete distribution based large-scale data processing framework☆2Updated 6 years ago
- Restricted Boltzmann Machines in R☆36Updated 3 years ago
- A quick educational implementation of a random forest classifier and a decsion jungle classifier.☆28Updated 9 years ago
- Sequential model-based optimization with a `scipy.optimize` interface☆14Updated 7 years ago
- Software for learning sparse Bayesian networks☆43Updated 4 years ago
- ☆32Updated 4 years ago
- Material for open source machine learning practical☆21Updated 9 years ago
- Torch package for metric learning.☆44Updated 7 years ago
- Introductory Workshop to (Bayesian) Statistics☆38Updated 7 years ago
- Code and data for "The Geometry of Classifiers"☆26Updated 4 years ago
- Talk on "Bayesian optimisation", beginner level☆25Updated 8 years ago
- Models, scripts, and data sets for data annotation (aka coding, aka rating)☆12Updated 9 years ago
- Code and text for our NIPS 2015 paper on linear response variational Bayes☆19Updated 6 years ago
- Course materials for STA663☆37Updated 8 years ago
- Bayesian Poisson Tucker decomposition☆17Updated 7 years ago
- The pdf and LaTeX for each paper (and sometimes the code and data used to generate the figures).☆73Updated 7 years ago
- Code to accompany the paper "k-Stochastic Neighbor Embeddings for Supervised and Unsupervised Learning, ICML 2013".☆27Updated 8 years ago
- The information sieve for discrete variables.☆35Updated 7 years ago
- Run Nx2 Cross Validation for multiple binary classifiers in parallel with optional downsampling☆13Updated 9 years ago
- Torch implementation of the Deep Network for Global Optimization (DNGO)☆51Updated 8 years ago
- Course offered online through Stanford closely following the text "An Introduction to Statistical Learning, with Applications in R" (Jame…☆5Updated 6 years ago