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Chrome extension meant to neutralize Admiral's very evil Adblock Recovery 👿

Home Page: https://chrome.google.com/webstore/detail/admiral-sucks/bhkgjcmhgbpmedkghbphnfkjibekjdgp?hl=en-US&authuser=0

License: The Unlicense

JavaScript 100.00%
adblocker ad-blocker chrome-extension paywall admiral

admiral-sucks's Introduction

Hello there! 👋🏻

Jérémie's dynamically generated GitHub stats

Jérémie's Mastodon Jérémie's Twitter Jérémie's Github Jérémie's ORCID Jérémie's GoogleScholar Jérémie's LinkedIn

Faculty at University of Pennsylvania's Department of Computer & Information Sciences. I love to teach, to mentor and advise students, to think "at scale", to build stuff open source, and to expand the circle of people who identify as "programmers."

  • 🔭 I’m currently working on music digital humanities project + CS education, code grading/teaching projects
  • 🌱 I’m currently learning TypeScript/React/front-end + machine learning
  • 👯 I’m looking to collaborate on open-source projects, especially that reduce the friction to building
  • 💬 Ask me about scaling, academic peer review, gamification, centralization/decentralization, capitalism, good software engineering practices, veganism 🐮

🎹 Tools for Musical Digital Humanities

  • 🎶 imslp: A Python package to query and retrieve scores from the International Music Score Library Project (IMSLP).

  • 🎼 incipit: A Python package and command line tool to slice a musical score into bars, staves and systems. Was originally designed to extract the first line of each of Domenico Scarlatti's 555 sonatas to create a searchable catalog with incipit.

You can also visit the GitHub organization of the Domenico Scarlatti Foundation.

⚙️ GitHub Templates for your projects

🎲 Probabilistic Algorithms

  • 🌊 Many data streaming probabilistic algorithms, including those I design and study, use families of hash functions. Hard to find families with good properties (simple, efficient, not too correlated). A affine transform of CRC32 hash, with factors drawn from Mersenne Twister provides a good empirical family. Details are tricky to get right—so I get them right for you!

  • 🙆🏼 Affirmative Sampling (2022) with Conrado Martínez (PDF), is a novel probabilistic sampling algorithm of which the size of the sample grows as a function of the (unknown) number of distinct elements, making it uniquely adaptive to queries that depend on the relative proportion of elements. Reference implemented in Python at affirmative-sampling

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