Transfer learning

Korean researchers borrow norm conservation from quantum circuits to design hydrogen catalysts

A team in Korea added orthogonal transformations to a generative model so fine-tuning would stop warping its latent space, and says the result becomes useful for hydrogen-evolution catalysts once transfer learning adds data.