Tolga Birdal

TNOs redefine operator learning by leveraging topological structures, achieving superior accuracy in complex PDE problems while maintaining physical fidelity.

Forget about trace norms – generalization in chaotic training regimes hinges on the intricate structure of the full Hessian spectrum and its partial determinants.

Ditch the flat scene graphs: TopoOR models surgical environments as higher-order topological structures, unlocking superior performance in safety-critical tasks by preserving complex relationships and multimodal data.

Forget interference as just noise: correlated features in neural networks can constructively superpose to form semantic clusters, especially with weight decay.