#numpyro resultados da pesquisa
I've been making progress on my #Bayesian inference in #python book draft. Latest addition is the multi-level modelling chapter. Check it out and then post your feedback here. Thanks! #numpyro Book: persuasivepython.com/13-multilevel
A JAX custom VJP function for multiple input variable does not work for NumPyro/HMC-NUTS stackoverflow.com/questions/6568… #numpyro #jax #pyroai #python
生徒の"学力の伸び"、どう測る？ 🤔 #ドワンゴ の教育事業のデータサイエンティストがPythonライブラリ #NumPyro を使った実装を解説 📝 ベイズ推定の結果診断や学力調査でも使われる「垂直尺度化」など、一歩踏み込んだ内容も扱っています。ぜひご覧ください 👇 blog.nnn.dev/entry/2025/10/… #Python…
Our paper on a JAX-based high-res exoplanet/BD spectrum model has been accepted by ApJS. arxiv.org/abs/2105.14782 #jax #numpyro
#NumPyro interface is so clean that I think I will plan to give some weight to it in my next projects.
Simple #rstats install - works on ALL platforms (see readme for more). Just four steps. Please test this #numpyro version before I release to CRAN.🙏 install.packages("remotes") remotes::install_github("flyaflya/causact") library(causact) install_causact_deps()
ExoJAX v1.1.0 released. #numpyro HMC reverse mode, optimization by #JAXopt, and VALD3 (metal lines) available: github.com/HajimeKawahara…
#numpyro をwindows10にインストールできた。 WindowsServerでベイズ統計モデルのアプリが作れる！ #streamlit の組み合わせも面白そう！ pip install jaxlib-*-win_amd64.whl pip install jax pip install numpyro pip install arviz qiita.com/FORETUNE/items…
qiita.com
【高速なnumpy】WindowsでJAXを使おう【Python】 - Qiita
この記事ではJust-In-Timeコンパイルにより高速計算を実現するライブラリJAXをWindowsに導入する手順を説明します。 JITコンパイル、JAXの説明はしません。 【参考】https://github.com/cloudhan/jax-windows-build...
{causact} 📦 v0.5.7 is on its way to CRAN. Visualize your Bayesian modelling assumptions using #rstats and get lightning fast inference using #numpyro for free. Give it a try!
{causact} 📦 helps you communicate your Bayesian modelling assumptions using #rstats. Can you spot the difference in these 3 Bayesian models?
It's shockingly fast, and installing #numpyro on Windows, which used to be difficult, now works perfectly. They are also working on automatic marginalization of unobserved discrete random variables... looking forward to trying that out.
#Albumentations - A Python library for image augmentation #Numpyro - A library that enables users to build probabilistic models using the Python programming language. #Torchscript - TorchScript is a library in #PyTorch
The {causact}📦 is bringing #numpyro speed to #rstats. Learning computational #Bayesian inference has never been easier. 🐣Install with ease 📊Build visual models with DAGs 🚅Automate Inference at #numpyro speed Test the #numpyro version from github: github.com/flyaflya/causa…
github.com
GitHub - flyaflya/causact: causact: R package to accelerate computational Bayesian inference...
causact: R package to accelerate computational Bayesian inference workflows in R through interactive visualization of models and their output. - flyaflya/causact
It's #Numpyro+Jax since it was easy to get lots of example problems, but as a Julia stan gotta say it was really easy and pleasant to use 👏
For my first post on twitter, I present to the world an astronomer friendly guide to taking your first steps with #NumPyro: hughmcdougall.github.io/blog/02_numpyr…
"Statistical Rethinking (2nd ed.) with #NumPyro" - "a small #ProbabilisticProgramming library provides a #NumPy backend for #Pyro" "powered by #JAX for autograd & JIT compilation to #GPU/CPU" distributions module follows #PyTorch bit.ly/2NSQfUE github.com/pyro-ppl/numpy…
Just having fun using NumPyro and JAX to do inference for ODE parameters - this finishes the translation of @rlmcelreath's Statistical Rethinking 2nd ed. book (latest draft version) to NumPyro fehiepsi.github.io/rethinking-num…
There are good tools in #rstats (e.g. Robyn) and #python (lightweightmmm), but as noted in the article, you often will just have to roll your own (e.g. via @mcmc_stan or #numpyro).
Ayer estuve de cena con @gilbellosta y con @r_vaquerizo alias "el frecuentista". Después de la cena @gilbellosta me casi convenció de que #numpyro es el futuro de lo bayesiano. Y he de reconocer que ha supuesto un gran avance. Ya no le puedo decir eso de que se acaba el ...
RT @preposterior@qoto.org I've been making progress on my #Bayesian inference in #python book draft. Latest addition is the multi-level modelling chapter. Check it out and then post your feedback here. Thanks! #numpyro BOOK Link: (1/2)
Para los que no hablamos vuestro idioma, @gilbellosta y @joscani: ¿Qué casos de uso resolvéis vosotros con #numpyro?
Ayer estuve de cena con @gilbellosta y con @r_vaquerizo alias "el frecuentista". Después de la cena @gilbellosta me casi convenció de que #numpyro es el futuro de lo bayesiano. Y he de reconocer que ha supuesto un gran avance. Ya no le puedo decir eso de que se acaba el ...
生徒の"学力の伸び"、どう測る？ 🤔 #ドワンゴ の教育事業のデータサイエンティストがPythonライブラリ #NumPyro を使った実装を解説 📝 ベイズ推定の結果診断や学力調査でも使われる「垂直尺度化」など、一歩踏み込んだ内容も扱っています。ぜひご覧ください 👇 blog.nnn.dev/entry/2025/10/… #Python…
生徒の"学力の伸び"、どう測る？ 🤔 #ドワンゴ の教育事業のデータサイエンティストがPythonライブラリ #NumPyro を使った実装を解説 📝 ベイズ推定の結果診断や学力調査でも使われる「垂直尺度化」など、一歩踏み込んだ内容も扱っています。ぜひご覧ください 👇 blog.nnn.dev/entry/2025/10/… #Python…
{causact} 📦 v0.5.7 is on its way to CRAN. Visualize your Bayesian modelling assumptions using #rstats and get lightning fast inference using #numpyro for free. Give it a try!
{causact} 📦 helps you communicate your Bayesian modelling assumptions using #rstats. Can you spot the difference in these 3 Bayesian models?
For my first post on twitter, I present to the world an astronomer friendly guide to taking your first steps with #NumPyro: hughmcdougall.github.io/blog/02_numpyr…
There are good tools in #rstats (e.g. Robyn) and #python (lightweightmmm), but as noted in the article, you often will just have to roll your own (e.g. via @mcmc_stan or #numpyro).
The {causact}📦 is bringing #numpyro speed to #rstats. Learning computational #Bayesian inference has never been easier. 🐣Install with ease 📊Build visual models with DAGs 🚅Automate Inference at #numpyro speed Test the #numpyro version from github: github.com/flyaflya/causa…
github.com
GitHub - flyaflya/causact: causact: R package to accelerate computational Bayesian inference...
causact: R package to accelerate computational Bayesian inference workflows in R through interactive visualization of models and their output. - flyaflya/causact
It's shockingly fast, and installing #numpyro on Windows, which used to be difficult, now works perfectly. They are also working on automatic marginalization of unobserved discrete random variables... looking forward to trying that out.
Simple #rstats install - works on ALL platforms (see readme for more). Just four steps. Please test this #numpyro version before I release to CRAN.🙏 install.packages("remotes") remotes::install_github("flyaflya/causact") library(causact) install_causact_deps()
#Albumentations - A Python library for image augmentation #Numpyro - A library that enables users to build probabilistic models using the Python programming language. #Torchscript - TorchScript is a library in #PyTorch
Para los que no hablamos vuestro idioma, @gilbellosta y @joscani: ¿Qué casos de uso resolvéis vosotros con #numpyro?
Ayer estuve de cena con @gilbellosta y con @r_vaquerizo alias "el frecuentista". Después de la cena @gilbellosta me casi convenció de que #numpyro es el futuro de lo bayesiano. Y he de reconocer que ha supuesto un gran avance. Ya no le puedo decir eso de que se acaba el ...
Ayer estuve de cena con @gilbellosta y con @r_vaquerizo alias "el frecuentista". Después de la cena @gilbellosta me casi convenció de que #numpyro es el futuro de lo bayesiano. Y he de reconocer que ha supuesto un gran avance. Ya no le puedo decir eso de que se acaba el ...
RT @preposterior@qoto.org I've been making progress on my #Bayesian inference in #python book draft. Latest addition is the multi-level modelling chapter. Check it out and then post your feedback here. Thanks! #numpyro BOOK Link: (1/2)
A JAX custom VJP function for multiple input variable does not work for NumPyro/HMC-NUTS stackoverflow.com/questions/6568… #numpyro #jax #pyroai #python
I've been making progress on my #Bayesian inference in #python book draft. Latest addition is the multi-level modelling chapter. Check it out and then post your feedback here. Thanks! #numpyro Book: persuasivepython.com/13-multilevel
Our paper on a JAX-based high-res exoplanet/BD spectrum model has been accepted by ApJS. arxiv.org/abs/2105.14782 #jax #numpyro
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