Deep Learning for Symbolic Mathematics | paper EXPLAINED

Deep Learning for Symbolic Mathematics | paper EXPLAINED

Jun 09, 2021
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Ms. Coffee Bean explains, draws and animates how neural networks can solve symbolic mathematics problems, e.g. integration, ODEs. It can even tackle integrals that Mathematica fails to solve. Do not worry, Mathematica, you are still awesome! Amazing work by Guillaume Lample and François Charton @Facebook AI . 📄 Lample, Guillaume, and François Charton. "Deep learning for symbolic mathematics." arXiv preprint arXiv:1912.01412 (2019). https://arxiv.org/pdf/1912.01412.pdf 📺 Ms. Coffee Bean explains the Transformer: https://youtu.be/FWFA4DGuzSc Outline: * 00:00 Neural networks integrate and solve ODEs. So what? * 03:55 Generating training data * 06:42 Representing and generating random functions * 07:56 Symbolic equations with neural nets Music 🎵 : Pretty Boy by DJ Freedem ----------------- 🔗 Links: YouTube: https://www.youtube.com/AICoffeeBreak Twitter: https://twitter.com/AICoffeeBreak Reddit: https://www.reddit.com/r/AICoffeeBreak/ #AICoffeeBreak #MsCoffeeBean #MachineLearning #AI #research​ #mathematics

00:00 Neural networks integrate and solve ODEs. So what? 03:55 Generating training data 06:42 Representing and generating random functions 07:56 Symbolic equations with neural nets
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