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pi-Net: Empirical Latent Representations for Differentiable Physics Heads in Data-Scarce Systems
Developing reliable predictive models for multi-physics systems often forces a compromise between computationally demanding physical simulators and data-hungry, opaque machine learning (ML) algorithms. While incorporating dimensional analysis into directed computation graphs offers a structurally so
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