Top Tweets for #PyStan
Developing #BayesianInference methods for complex scientific problems?
#EuroSciPy2025 is seeking original work on Hamiltonian Monte Carlo, variational inference, and statistical modeling in #Python.
#CfP: https://t.co/Yq0LqTzjlW
#ScientificPython #PyMC #PyStan #EuroSciPy
おはようございます☀
毎週水曜日はスキルアップAI無料勉強会の日😁
来週のテーマは
「統計的仮説検定とベイズ推定」
※本セミナーは、第81回の再配信となります
従来の仮説検定とベイズ統計学に基づく仮説検定の基礎知識と、PyStanによる実装方法を紹介👍
https://t.co/rYoWYlesCV
#PyStan
#Forecasting Website Traffic Using #Facebook’s #Prophet Library
https://t.co/wwNswmMjQi
#AI #MachineLearning #SupervisedLearning #Regression #ForecastingModels #analytics #Python #R #pystan #fbprophet #pandas #numpy #DataFrame #make_future_dataframe #predict
#100DaysOfCode Day 3: I wrote a notebook demo-ing #PyStan modeling with a 1-armed bandit
https://t.co/vIi5HVk8JE
The code behind this paper is public! Cool enough that they've used #pystan. If you are unfamiliar with @mcmc_stan, they've also written a tutorial (https://t.co/hyPKX4xLWG). What a lovely combination! 🌺
Very fulfilling work with @_jgyou and Mark Newman in @UMichCS on developing better techniques to infer the network structure of #MutualisticNetworks #EcologicalNetworks. Looking forward to more of this fantastic collaboration! https://t.co/mRbGWnxL0y
Get an introduction to #bayesian modeling in #PyStan #mathematics #statisticalmodeling https://t.co/2bqBHxyWi7
Software Update 2019-01-12
#RStan #PyStan, #JuMP and #IpOpt for @JuliaLanguage, and more fonts for #LuaTeX (e.g. @OpenDyslexic)
https://t.co/ItQN3St5VE
Now maintaining an up to date #pystan package on the AUR : https://t.co/KubK0NlHu0
Archlinux users please upvote ⬆️⬆️ @mcmc_stan
I wrote a blog post about a bunch of ways to generate/plot uncertainty estimates https://t.co/OdumNDpQtS
Bayesian Methods for Hackers by @Cmrn_DP ported to #Tensorflow Probability (TFP) by @mikeshwe & the Google TFP team. https://t.co/DWzHBpFfhi
Great way to learn TFP albeit it's less user-friendly than #PyMC3 or #PyStan
#ProbabilisticProgramming #ProbabilisticModeling #AI
What’s the status of multi-threading in @mcmc_stan (specifically #pystan)? I know that there was promising work on it a year ago, but is it available to end users?
Some really great discussion on a collaboration between #PyMC3, #Edward, #PyStan and #Pyro on a common trace storage object using #xarray which would allow everyone to use ArviZ (#PyMC3's plotting functionality broken out) https://t.co/lRQc2Rwsby HT @aseyboldt @aloctavodia
I have finally have attempted to expand my knowledge of #MCMC samplers by giving #PyMC3 @pymc_devs and #PyStan a go. Unsurprisingly, they will sample the posterior distributions of the gradient and y-intercept of a straight line using a Gaussian likelihood quite easily https://t.co/IvWzv6a57x
We'll hopefully be adding samplers other than #emcee soon-ish. As such, to figure out how to code them up, I've attempted a toy example using #PyMC3 @pymc_devs ()https://t.co/wfFiuwTwU9 and #PyStan @mcmc_stan (https://t.co/fRTUsN74L2)
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