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math.OC2026
Training Infinitely Deep and Wide Transformers
Raphaël Barboni, Maarten V. de Hoop, Takashi Furuya +1
Transformers have become the dominant architecture in modern machine learning, yet the theoretical understanding of their training dynamics remains limited. This paper develops a r…
math.OC2026
Boundary observability for gas giant metrics
Maarten V. de Hoop, Antti Kykkänen, Emmanuel Trélat
We study the observability of waves on gas giant manifolds which are a class of Riemannian manifolds whose metrics are singular at the boundary. Such manifolds arise naturally in m…