The Geometry-Aware Generative Autoencoder (GAGA) framework combines extensible manifold learning with generative modeling to address computational and statistical challenges in geometry-aware data generation, trajectory interpolation, and population transport.

Authors

• Person: Samuel Tesfazgi, Leonhard Sprandl, Sandra Hirche Organization: AISTATS
  Track: Poster Session 3 - aistats 2026

Sources

• Track: Poster Session 3 - aistats 2026 virtual.aistats.org Samuel Tesfazgi, Leonhard Sprandl, Sandra Hirche · AISTATS via serper

Referenced by nodes (1)

• generative models concept