Residual Neural Networks – cmc.deusto.eus

Large-time asymptotics in deep learning

deep learning, Neural ODEs, optimal control, Residual Neural Networks, Supervised Learning, turnpike property

C. Esteve, B. Geshkovski, D. Pighin, E. Zuazua (2025) Large-time asymptotics in deep learning, https://hal.archives-ouvertes.fr/hal-02912516 Abstract. We consider the neural ODE perspective of supervised learning and study the impact of the…

Turnpike Control and Deep Learning by Enrique Zuazua at IITK

deep learning, Neural ODEs, optimal control, Residual Neural Networks, Supervised Learning, turnpike property

Worldwide. 08.09.2020. Yesterday, our Head Enrique Zuazua gave a talk about "Turnpike Control and Deep Learning" hosted by IITK - Indian Institute of Technology, Kampur in collaboration with IISER-Kolkata, IISER-Pune,…

Turnpike Control and Deep Learning at IITK by E. Zuazua

Next tuesday September 8th, our Head Enrique Zuazua will present "Turnpike Control and Deep Learning" on the IITK research seminars organized by IITK- Indian Institute of Technology, Kanpur in collaboration with…

Turnpike Control and Deep Learning – Fields Institute 2nd Simposium on Machine Learning and Dynamical Systems

deep learning, Neural ODEs, optimal control, Residual Neural Networks, Supervised Learning, turnpike property

Worldwide. 01.09.2020. The Fields Institute for Research in Mathematical Sciences at the University of Toronto, Canada organized the Second Simposium on Machine Learning and Dynamical Systems on September 21st to…

Large-time asymptotics in deep learning

Turnpike Control and Deep Learning by Enrique Zuazua at IITK

Turnpike Control and Deep Learning at IITK by E. Zuazua

Turnpike Control and Deep Learning – Fields Institute 2nd Simposium on Machine Learning and Dynamical Systems

Clustering in Pure-Attention Hardmax Transformers and its Role in Sentiment Analysis

A potential game perspective in Federated Learning

Regional and Partial Observability and Control of Waves

Cluster-based classification with neural ODEs via control

Optimal convergence rates for the finite element approximation of the Sobolev constant