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bayesian
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Python for《Deep Learning》，该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现
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Jun 23, 2020 - Python
rok-cesnovar
commented
Nov 19, 2021
Description:
We need some easy to follow instructions on how to use the core Stan inside a user-written C++ program. See stan-dev/stan#3085 for example.
The instruction can simply guide through the task of compiling one of the models and running MCMC with the services. The biggest challenges are typically all the dependencies that we need to include in the C++
serenabooth
commented
Oct 30, 2019
Ankit Shah and I are trying to use Gen to support a project and would love the addition of a dirichlet distribution
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
python
machine-learning
time-series
orbit
regression
pytorch
forecast
bayesian-methods
forecasting
probabilistic-programming
bayesian
stan
arima
regression-models
probabilistic
bayesian-statistics
pyro
changepoint
pystan
exponential-smoothing
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Apr 7, 2022 - Python
Seminars DeepBayes Summer School 2018
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Aug 24, 2019 - Jupyter Notebook
Bayesian Data Analysis demos for Python
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Dec 16, 2021 - Jupyter Notebook
GemPy is an open-source, Python-based 3-D structural geological modeling software, which allows the implicit (i.e. automatic) creation of complex geological models from interface and orientation data. It also offers support for stochastic modeling to adress parameter and model uncertainties.
python
theano
interpolation
modeling
geoscience
bayesian
monte-carlo-simulation
implicit
uq
geology
uncertainties
uncertainty-analysis
complex-geological-models
geological
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Apr 6, 2022 - Python
How to do Bayesian statistical modelling using numpy and PyMC3
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Aug 2, 2021 - Jupyter Notebook
A collection of Bayesian data analysis recipes using PyMC3
notebook
bayesian-methods
neural-networks
bayesian
bayesian-inference
bayesian-data-analysis
bayesian-statistics
bayesian-analysis
treatment-groups
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Dec 27, 2021 - Jupyter Notebook
r
apa
reporting
models
automatic
reports
report
rstats
scientific
bayesian
manuscript
hacktoberfest
statsmodels
describe
automated-report-generation
easystats
anovas
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Apr 3, 2022 - R
Bayesian Data Analysis demos for R
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Mar 25, 2022 - R
map
r
rstats
bayesian
hacktoberfest
rope
bayes-factors
posterior-distributions
hdi
bayesfactor
easystats
credible-interval
bayesian-framework
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Apr 7, 2022 - R
Python package for Bayesian Machine Learning with scikit-learn API
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Sep 22, 2021 - Jupyter Notebook
A python library for Bayesian time series modeling
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Feb 24, 2021 - Python
Bayesian Deep Learning: A Survey
machine-learning
deep-learning
survey
neural-networks
bayesian
arxiv
bayesian-deep-learning
variational-autoencoders
bdl
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Mar 5, 2022
High-performance Bayesian Data Analysis on the GPU in Clojure
machine-learning
clojure
statistics
gpu
opencl
cuda
clojure-library
high-performance-computing
gpu-acceleration
bayesian
gpu-computing
bayesian-inference
mcmc
bayesian-data-analysis
markov-chain-monte-carlo
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Sep 10, 2020 - Clojure
bayesplot R package for plotting Bayesian models
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Mar 31, 2022 - R
rstanarm R package for Bayesian applied regression modeling
r
bayesian-methods
rstan
bayesian
multilevel-models
bayesian-inference
stan
r-package
rstanarm
bayesian-data-analysis
bayesian-statistics
statistical-modeling
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Apr 8, 2022 - R
r
correlation
matrix
regression
outliers
robust
bayesian
gamma
hacktoberfest
partial
gaussian-graphical-models
cor
correlations
correlation-analysis
spearman
partial-correlations
easystats
bayesian-correlations
multilevel-correlations
biserial
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Mar 31, 2022 - R
Collection of probabilistic models and inference algorithms
python
machine-learning
bayesian
bayesian-inference
mcmc
variational-inference
gibbs-sampling
dirichlet-process
probabilistic-models
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Apr 3, 2020 - Python
ELFI - Engine for Likelihood-Free Inference
python
statistics
simulator
anaconda
engine
gitter-chat
inference
bayesian
bayesian-inference
notebooks
likelihood-free
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Apr 7, 2022 - Python
A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.
machine-learning
optimization
hyperparameter-optimization
bayesian
gaussian-processes
bayesian-optimization
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Feb 4, 2020 - C++
Implementation of robust dynamic Hamiltonian Monte Carlo methods (NUTS) in Julia.
julia
julia-language
bayesian-methods
bayesian
bayesian-inference
hamiltonian-monte-carlo
bayesian-statistics
hybrid-monte-carlo
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Oct 7, 2021 - Julia
Bayesian multi-object tracking
optimization
bayesian
object-tracking
kalman-filter
multi-object-tracking
cell-tracking
tracking-algorithm
btrack
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Apr 8, 2022 - C++
shinystan R package and ShinyStan GUI
r
bayesian-methods
bayesian
bayesian-inference
stan
r-package
shiny-apps
statistical-graphics
mcmc
bayesian-data-analysis
bayesian-statistics
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Mar 3, 2022 - R
PyTorch implementation of bayesian neural network.
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Oct 22, 2021 - Python
Code that might be useful to others for learning/demonstration purposes, specifically along the lines of modeling and various algorithms. Now almost entirely superseded by the models-by-example repo.
python
r
julia
zip
matlab
irt
pca
survival-analysis
bayesian
stan
em
mixture-model
factor-analysis
gaussian-processes
jags
mixed-models
additive-models
lasso-regression
ordinal-regression
probit
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Nov 25, 2020 - R
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NumPyro now has several excellent introductory examples with no direct counterparts in Pyro. Porting one of these to Pyro would be a great way for someone to simultaneously learn more about Bayesian data analysis and make a valuable open source contribution.
If you are reading this and want to give one of them a try, please leave a comment here so that other peo