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afshinea / Stanford Cme 295 Transformers Large Language ModelsVIP cheatsheet for Stanford's CME 295 Transformers and Large Language Models
paul-buerkner / Brmsbrms R package for Bayesian generalized multivariate non-linear multilevel models using Stan
TheEconomist / Us Potus ModelCode for a dynamic multilevel Bayesian model to predict US presidential elections. Written in R and Stan.
stan-dev / MathThe Stan Math Library is a C++ template library for automatic differentiation of any order using forward, reverse, and mixed modes. It includes a range of built-in functions for probabilistic modeling, linear algebra, and equation solving.
stan-dev / Example ModelsExample models for Stan
modelica / ModelicaStandardLibraryFree (standard conforming) library to model mechanical (1D/3D), electrical (analog, digital, machines), magnetic, thermal, fluid, control systems and hierarchical state machines. Also numerical functions and functions for strings, files and streams are included.
sibylhe / Mmm StanPython/STAN Implementation of Multiplicative Marketing Mix Model, with deep dive into Adstock (carry-over effect), ROAS, and mROAS
stan-dev / PystanPyStan, a Python interface to Stan, a platform for statistical modeling. Documentation: https://pystan.readthedocs.io
stan-dev / CmdstanpyCmdStanPy is a lightweight interface to Stan for Python users which provides the necessary objects and functions to compile a Stan program and fit the model to data using CmdStan.
SciML / ModelingToolkitStandardLibrary.jlA standard library of components to model the world and beyond
sinhrks / Stan StatespaceStan models for state space time series
MatsuuraKentaro / Bayesian Statistical Modeling With Stan R And PythonKentaro Matsuura (2022). Bayesian Statistical Modeling with Stan, R, and Python. Springer, Singapore.
hammerlab / SurvivalstanLibrary of Stan Models for Survival Analysis
roualdes / BridgestanBridgeStan provides efficient in-memory access through Python, Julia, and R to the methods of a Stan model.
liang456 / Stanford Probabilistic Graphical Models CourseraNo description available
jhoupt / DBDA2EstanStan implementations of models in Doing Bayesian Data Analysis, 2nd Edition
logics-of-blue / Book R Stan Bayesian Model IntroNo description available
bayesianops / Stan Survival Model WorkshopBuilding a Survival Model in Stan.
saudiwin / Idealstanidealstan offers item-response theory (IRT) ideal-point estimation for binary, ordinal, counts and continuous responses with time-varying and missing-data inference. Latent space model also included. Full and approximate Bayesian sampling with 'Stan' (www.mc-stan.org).
flatironinstitute / Stan PlaygroundRun Stan models in the browser
