Stochastic waveforms are intrinsic to many physical and telecommunication processes, yet reproducible interfaces for converting them into compact stochastic representations suitable for ...

This library supports calculation of uniform boundaries, confidence sequences, and always-valid p-values. These constructs are useful in sequential A/B testing, best-arm identification, and other ...

Machine learning (ML) and artificial intelligence (AI) techniques are transforming the way chemical reactions are studied today. Datasets from high-throughput experimentation (HTE) are generated to ...

Credit risk modelling is a cornerstone of modern finance, enabling lenders to quantify the risk that a borrower will default on their obligations. One of the most important metrics in this domain is ...

Epistasis - the interaction between alleles at different genetic loci - plays a fundamental role in biology. However, several recent approaches quantify epistasis using a chimeric formula that ...

particle filtering: bootstrap filter, guided filter, APF. resampling: multinomial, residual, stratified, systematic and SSP. possibility to define state-space models using some (basic) form of ...

A full-code demo from Dr. James McCaffrey of Microsoft Research shows how to predict the type of a college course by analyzing grade counts for each type of course. General naive Bayes classification ...

Bayesian Decision Trees provide a probabilistic framework that reduces the instability of Decision Trees while maintaining their explainability. While Markov Chain Monte Carlo methods are typically ...

I recently prepared a multiple-choice quiz on LinkedIn, which asked, "What is the probability of a 100-year event (or greater) occurring at least once in 100-years?" Although this seems like a ...

Thompson Sampling is an algorithm that can be used to analyze multi-armed bandit problems. Imagine you're in a casino standing in front of three slot machines. You have 10 free plays. Each machine ...