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Found 3 papers, 2 papers with code
Learning effective good variables from physical data
We assume that a sufficiently large database is available, where a physical property of interest and a number of associated ruling primitive variables or observables are stored.
On some elusive aspects of databases hindering AI based discovery: A case study on superconducting materials
It stands to reason that the amount and the quality of big data is of key importance for setting up accurate AI-driven models.
Double Diffusion Maps and their Latent Harmonics for Scientific Computations in Latent Space
A second round of Diffusion Maps on those latent coordinates allows the approximation of the reduced dynamical models.
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