Build your own Face App with Stable Diffusion 2.1
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Updated
Sep 27, 2024 - Jupyter Notebook
Build your own Face App with Stable Diffusion 2.1
Sampling particles on a hypersurface with local event-by-event account of energy, momentum, baryon number, strangeness and charge conservation.
An open-source JAX-based statistical sampling toolkit 🧪
A modern Fortran statistical library.
Analysis of mock A/B Test Results by an e-commerce company. Application of probability, hypothesis testing, sampling distribution, two-sample z-test, and logistic regression to determining whether the company should implement the new web page it developed to increase users' conversion rate
Tools to support the Discrete-Event Simulation process for education and practice.
Rhombic grids for coherent plane-wave compounding (CPWC) in ultrasound imaging
Tutorial: A simple GAN to generate samples from Gaussian distribution
Demonstrates reverse annealing on D-Wave quantum computers.
Some R and Python code I've been working on.
Package provides python implementation of statistical inference engine
Use bootstrap resampling to estimate the sampling distribution of a statistic
This takes any Pandas or Dask dataframe and returns a resampled Dask dataframe simulating the sampling distribution of your data in one line of code. This is like the rep_sample_n() function from the infer package in R, but on steroids and made for quickly simulating a large number of replicate samples and even with a large number of observation…
A/B tests are very commonly performed by data analysts and data scientists. It is important that you get some practice working with the difficulties of these.
This code can be used to reproduce the results in our paper ``A Control Approach for Nonlinear Stochastic State Uncertain Systems with Probabilistic Safety Guarantees''.
Applying A/B test to help determing if company should launch the new page
working to understand the results of an A/B test run by an e-commerce website. The company has developed a new web page in order to try and increase the number of users who "convert," meaning the number of users who decide to pay for the company's product.
Likelihood model framework
Sampling Distribution and Hypothesis testing with [learnwithfair, Learn with fair, Rahatul Rabbi, Md Rahatul Rabbi ,rahatulrabbi]
The repository covers some of the key concepts of Inferential Statistics with the help of R.
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