The promise of this tutorial: the companion tutorial on Ψ-NN ended with a triumph: a neural network that can’t break a law of physics, and that learns how to be that way on its own. But that network had a quiet problem: it could only talk to other neural networks. This tutorial picks up exactly [...]
The promise of this tutorial: by the end you will understand, step by step, how Physics Structure-Informed Neural Network (Ψ-NN) takes an ordinary neural network and rebuilds it so that it literally cannot break a law of physics, and how it figures out how to do that all by itself. We will keep every idea [...]
Happy to announce that I’ve taken a meaningful step toward bridging the gap between AI and circuit/device modeling. It is my absolute pleasure to introduce Ψ-HDL (pronounced Psi-HDL), my Physics Structure-Informed Hardware Description Language framework. This work builds directly on the Ψ-NN (Physics structure-informed neural network) discovery framework introduced by Liu et al. (Nature Communications, [...]
Every so often, a paper comes along that feels like it bridges two worlds that have been talking past each other. Recently, I came across one of those papers: “Automatic network structure discovery of physics informed neural networks via knowledge distillation” by Ziti Liu and colleagues. It’s an ambitious piece of work that tries to [...]
Apparently, I’m a „German Travel Blogger“ NowSome Interesting Books I Recommend ReadingA From-Scratch Tutorial on Ψ-HDL (Psi-HDL) and Ψ-xLSTM (Psi-xLSTM)A From-Scratch Tutorial on Ψ-NN (Psi-NN)Better World Models for a Multipolar World
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