The increasing diversity of scientific and engineering data has driven the development of flexible techniques for inferring probability distributions without assuming a specific parametric family.

Nonparametric density estimation on Riemannian manifolds extends classical techniques to data that lie on curved spaces rather than in Euclidean domains. Such manifolds may arise as spheres, rotation ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

The showcase features works that change from hour to hour, invite interaction and interrogate the idea of creativity itself. “Heads-Tails” by Madeline HollanderCredit...Compiled by Manny Alcala Via ...

This event has ended! You can no longer find your Easter Code in Dress to Impress now that the Petal Update is here. Head to our Dress to Impress Petal Update 2025 - All Details and Patch Notes page ...

If you’d like an LLM to act more like a partner than a tool, Databot is an experimental alternative to querychat that also works in both R and Python. Databot is designed to analyze data you’ve ...

Set create_data and do_plotting to True and press play. Initiation is at the bottom of the script. Requires numpy, matplotlib, and scipy. adk_estimator: Contains the functions that does the adaptive ...

Researchers at the University of Waterloo’s Cheriton School of Computer Science in Canada found that modifying just 30 lines of code in the Linux kernel could cut data center energy consumption by 30% ...

This article is adapted from an edition of our Off the Charts newsletter originally published in October 2021. Off the Charts is a weekly, subscriber-only guide to The Economist’s award-winning data ...

One of the most useful new features that Microsoft has incorporated into Excel in recent years is the ability to incorporate Python code directly into a spreadsheet. While it has long been possible to ...

Abstract: This paper shows that adaptive kernel density estimator (KDE) can be derived effectively from Isolation Kernel. Existing adaptive KDEs often employ a data independent kernel such as Gaussian ...