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ml-jku · Oct 8, 2024 · 75da126 · 75da126
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 # Universal Physics Transformer (UPT)
 
-[[`Project Page`](https://ml-jku.github.io/UPT)] [[`Paper (arxiv)`](https://arxiv.org/abs/2402.12365)] [[`Codebase Demo Video`](https://youtu.be/80kc3hscTTg)] [[`BibTeX`](https://github.com/ml-jku/UPT#citation)]
+[[`Project Page`](https://ml-jku.github.io/UPT)] [[`Paper`](https://arxiv.org/abs/2402.12365)] [[`Talk`](https://youtu.be/mfrmCPOn4bs)] [[`Tutorial`](https://github.com/BenediktAlkin/upt-tutorial)] [[`Codebase Demo Video`](https://youtu.be/80kc3hscTTg)] [[`BibTeX`](https://github.com/ml-jku/UPT#citation)]
 
 # Train your own models
 

diff --git a/docs/index.md b/docs/index.md
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-[[Code](https://github.com/ml-jku/UPT)] [[Paper (arxiv)](https://arxiv.org/abs/2402.12365)] [[Codebase Demo Video](https://youtu.be/80kc3hscTTg)] [[BibTeX](https://github.com/ml-jku/UPT#citation)]
+[[Code](https://github.com/ml-jku/UPT)] [[Paper](https://arxiv.org/abs/2402.12365)] [[Talk](https://youtu.be/mfrmCPOn4bs)]  [[Tutorial](https://github.com/BenediktAlkin/upt-tutorial)] [[Codebase Demo Video](https://youtu.be/80kc3hscTTg)] [[BibTeX](https://github.com/ml-jku/UPT#citation)]
 
 
 **U**niversal **P**hysics **T**ransformers (UPTs) are a novel learning paradigm to efficiently train large-scale