While millions were taking Coursera courses and hearing, *"If you don’t understand it, it doesn’t matter,"* China’s elite coders were mastering an entirely different game. DeepSeek engineers, operating at an exceptional level, showcased x100 proficiency in both complex hardware and low-level programming.

Did you know that people tried to prove central limit theorem for over two centuries, first starting with de Moivre (1733), then almost a century after by Laplace who both used binomial distribution. Then it was Poisson who worked on this theorem, and Chebyshev (1890–1891) who gave a rigorous demonstration of it in the middle of the nineteenth century.

All you need is Kolmogorov–Arnold Network! 🔥🔥🔥 complete with GitHub repo 🚀🚀🚀🚀🚀

'KAN: Kolmogorov–Arnold Networks' from @MIT and @Caltech

h/t @illumattnati

code -> arxiv.org/abs/2404.19756
github.com/KindXiaoming/p…

Top 10 @github libraries for #conformalprediction Awesome Conformal Prediction - The most comprehensive professionally curated resource on Conformal Prediction by @predict_addict github.com/valeman/awesom…

Conformal prediction for #timeseries #forecasting is the hottest 🔥🔥🔥🔥 🚀🚀🚀🚀 area of research and applications right now.

The whole story started in summer 2021 when researchers from Georgia Tech published the first ever paper applying conformal prediction to time series. and presenting it at the first event at major conference totally dedicated to conformal prediction (ICML DFUQ 2021 organised by @ml_angelopoulos and @stats_stephen

@Zergylord @SchmidhuberAI Well unless you are top dog in DeepMind? Are you? @Zergylord @SchmidhuberAI Personally I find it hilarious that DeepMind is turning phd interns whilst some of its grunts can engage in trolling on Twitter during working time.

Motivated by having seen yet another Platt’s scaler post.

Platt’s scaling and isotonic regression are ~20 years old at this point. Both of them don’t have any mathematical guarantees of validity and are outperformed by conformal prediction Venn-ABERs

#conformalprediction VENN-ABERS is in fact a better regularised version of isotonic regression that constructors two isotonic regressions by postulating that a test object can a priori have both 0 and 1 as a label.

Another great development from @nixtlainc, ETS from StatsForecast is much more accurate and over 100 faster than NeuralProphet.

nice work @fede_gr and @nixtlainc team

#timeseries #forecasting Last year a few data scientists including myself exposed severe issues with facebook prophet resulting in facebook pulling down claims such as “with facebook prophet anyone can produce better forecasts than human experts “.