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9 Distance Measures in data science with algorithms (v/Dr. Ganapathi Pulipaka 🇺🇸).

This repository on ML operations has free talks, books, papers and more: bit.ly/MLops Developed by ÐR. VISΞNGΞRIYΞVΛ

Traditional Neural Networks are overrated. Transformer is irrelevant when we have a small set of unique examples. And no, brute-forcing with discrete program search is not the way too. It's so hilarious how easy, simple and yet elegant the actual approach is.

arxiv.org/abs/2408.12118 The main motivation for GW detectors should be to have a new set of eyes to look at the sky and learn about the universe. Finding physics beyond the SM/GR should not be pushed as a big motivation since it will backreact negatively 1/2

Another new benchmark shows: Aleatoric and epistemic uncertainty estimators are not disentangled. Great to this topic gaining momentum - IMO one of the most pressing issues in today's UQ! We'll release new results for our own uncertainty disentanglement benchmark aswell, soon™

For anyone curious about nonlinear dynamics and chaos, including students taking a first course in the subject: My lectures are freely available here. m.youtube.com/playlist?list=…

Videos of my lectures on "asymptotics and perturbation methods" are freely available. These are ingenious mathematical methods for analyzing difficult problems by exploiting the presence of a small parameter in them. Widely used in physics, math, CS,... youtube.com/playlist?list=…

we never thanked him enough

Studying up for the weekend.

back to school this week and back to reminding people that one of the coolest things my advisor did was write a course on how to build PyTorch from scratch if you want to become an expert on deep learning, can't think of a much better place to start than MiniTorch:

Introducing Project Sid: the first simulations of 1000+ truly autonomous agents collaborating in a virtual world, w/ emergent economy, culture, religion, and government Humans are the only species to land the moon, because we can cooperate at a vast scale Can AI do the same?

«Linear Algebra and Its Applications» by David & Steven Lay, and Judi McDonald is truly a masterpiece. A textbook teaching Linear Algebra geometrically, application first, with computer exercises and data sets, interactive figures, and projects. 🤩🤩🤩

Game changer for scraping. This GitHub repo lets you easily scrape web pages and have the output in LLM-friendly formats (JSON, cleaned HTML, markdown). Features • Supports crawling multiple URLs simultaneously • Extracts and returns all media tags (Images, Audio, and Video)

pair.withgoogle.com/explorables/

📢 I’m thrilled to write recommendation letters for 12 amazing Precogs applying to graduate schools for Fall 2025! 🎓✨ If you are a faculty (tagged some) at one of these Universities, keep an eye 👀 🧐 out for these applications and profiles (tagged below) . #ProfGiri (1/3)

🚨Great Models Think Alike and this Undermines AI Oversight🚨 New paper quantifies LM similarity (1) LLM-as-a-judge favor more similar models🤥 (2) Complementary knowledge benefits Weak-to-Strong Generalization☯️ (3) More capable models have more correlated failures 📈🙀 🧵👇

📣 #Newpaper🚨 Our work "Great Models Think Alike & this Undermines AI Oversight" 📜 arxiv.org/abs/2502.04313 🌐 model-similarity.github.io 📂 huggingface.co/datasets/bethg… w/ Shashwat Goel Joschka Strueber @ ICML2025 🇨🇦 Ilze Amanda Auzina Karuna Douwe Kiela Matthias Bethge Ameya P. @ ICML 2025 Jonas Geiping 🧵👇

📣Our work w/ Google DeepMind "Topo Goes Political: TDA-Based Controversy Detection in Imbalanced Reddit Political Data" accepted #BeyondFacts25 The Web Conference w/ Arvindh Arun Karuna Akshit Precog Research group at IIIT Hyderabad Balakumar, Jashn Arora, Manish Jain Paper: arxiv.org/abs/2503.03500 🧵👇

1/5 Spotlight: Great Models Think Alike, and this Undermines AI Oversight Tue 15th 11-1:30, East Exhibition Hall A-B E-2411 We show how to measure model similarity, how it trends with scaling, and effects on LLM-as-a-Judge and Weak-to-Strong. x.com/ShashwatGoel7/…