After I published my earlier blog post on Ψ-NN (Physics Structure-Informed Neural Networks), I received a very kind comment from one of the authors. In that reply, they pointed me to two earlier projects from the same research line: AsPINN (Adaptive Symmetry-Recomposition Physics-Informed Neural Networks) and AtPINN (Adaptive Transfer Learning for PINN). At first glance, [...]
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 [...]
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