[ICML2026] Solving the Problem of Data Scarcity Using Riemannian Geometry
LG AI Research uses Riemannian geometry to improve transfer learning for scarce scientific data.
Research paper
LG AI Research presented GEAR and Sim-GEAR at ICML 2026, two research projects that address data scarcity in materials science by using Riemannian geometry to improve transfer learning between physical property prediction models.
The method calculates curvature in the latent spaces of a data-rich source model and a data-poor target model, training them so their geometric structures become similar.
