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A unified, open-source framework and a massive 3.3 TB dataset now enable rigorous ML-driven prediction of complex multiphase flows in porous media, accelerating research in critical energy and engineering applications.
Achieve a 44% RMSE reduction in monocular depth estimation for colonoscopy by turning depth maps into an active generative foundation for sim-to-real adaptation.
