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bayesian
Here are 472 public repositories matching this topic...
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
Open
var_context builder
bob-carpenter
commented
May 23, 2020
Summary:
It'd be nice to have a builder pattern for var contexts to make them easy to construct for testing. Something that could be used like this:
MatrixXd m(3, 2);
...
var_context vc
= var_context::builder()
.matrix("a", m)
.real("f", 2.3)
.build();
Current Version:
v2.23.0
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
Seminars DeepBayes Summer School 2018
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Aug 24, 2019 - Jupyter Notebook
Bayesian Data Analysis demos for Python
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May 18, 2020 - 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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Sep 4, 2020 - Jupyter Notebook
Python package for Bayesian Machine Learning with scikit-learn API
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Jun 11, 2020 - Jupyter Notebook
How to do Bayesian statistical modelling using numpy and PyMC3
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Aug 5, 2020 - Jupyter Notebook
Bayesian Data Analysis demos for R
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Aug 28, 2020 - R
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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Jul 30, 2019 - Clojure
A python library for Bayesian time series modeling
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Jul 26, 2020 - Python
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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Sep 2, 2020 - Python
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Aug 31, 2020 - 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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Aug 28, 2020 - R
r
apa
reporting
models
reports
rstats
bayesian
manuscript
statsmodels
automated-report-generation
easystats
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Aug 26, 2020 - R
bayesplot R package for plotting Bayesian models
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Aug 30, 2020 - 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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Sep 2, 2020 - 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++
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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Aug 6, 2020 - R
yet another general purpose naive bayesian classifier.
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Sep 1, 2019 - Python
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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Sep 4, 2020 - Julia
Code that might be useful to others for learning/demonstration purposes, specifically along the lines of modeling and various algorithms.
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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Apr 19, 2020 - R
Tutorial on model assessment, model selection and inference after model selection
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Mar 22, 2019 - HTML
An interactive online reading of McElreath's Statistical Rethinking
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Jun 10, 2018 - Rebol
The Predictive Ecosystem Analyzer (PEcAn) is an integrated ecological bioinformatics toolbox.
data-science
r
university
fortran
doi
plants
forecasting
bayesian
meta-analysis
data-assimilation
effort
nc-sa
illinois
pecan
cyberinfrastructure
davidson
ecosystem-model
national-science-foundation
ecosystem-science
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Sep 4, 2020 - R
r
correlation
matrix
regression
bayesian
gaussian-graphical-models
correlations
partial-correlations
easystats
bayesian-correlations
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Jul 27, 2020 - R
Hierarchical Bayesian modeling of RLDM tasks, using R & Python
reinforcement-learning
modeling
decision-making
computational
bayesian
hierarchical-bayesian-analysis
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Sep 3, 2020 - Python
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To begin I tried logging in with GitHub and also creating an account on the pyro forums, but neither of those is working.
Problem
I need to fit a batch of four independent Gaussian Processes and I don't want to have to use for loops for fitting each one. The current GP's are able to broadcast properly to my outputs, but I can't batch them so that the inputs are independent.
My input d