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deep learning

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Neural ODE Control for Classification, Approximation and Transport

Tags: data classification, deep learning, Neural ODEs, Optimal Transport, simultaneous control, transport equations, universal approximation, Wasserstein distance
Ruiz-Balet D., Zuazua E. Neural ODE Control for Classification, Approximation and Transport (2022). SIAM Review Abstract. We analyze Neural Ordinary Differential Equations (NODEs) from a control theoretical perspective to address…
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Sparse approximation in learning via neural ODEs

Tags: deep learning, Neural ODEs, Nonlinear systems, optimal control, Sparsity, Supervised Learning
Esteve C., Geshkovski B. Sparse approximation in learning via neural ODEs (2021) Abstract. We consider the continuous-time, neural ordinary differential equation (neural ODE) perspective of deep supervised learning, and study the…
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Large-time asymptotics in deep learning

Tags: deep learning, Neural ODEs, optimal control, Residual Neural Networks, Supervised Learning, turnpike property
Esteve C., Geshkovski B., Pighin D., Zuazua E. Large-time asymptotics in deep learning (2021). hal-02912516 Abstract. It is by now well-known that practical deep supervised learning may roughly be cast as…
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HKSIAM Seminar by E. Zuazua: Turnpike control and deep learning

HKSIAM Seminar by E. Zuazua: Turnpike control and deep learning

Tags: deep learning, DL, Turnpike
Worldwide. This wednesday November 25th. our Head Enrique Zuazua will be talking about "Turnpike control and deep learning" in the Applied Mathematics Seminars for HKSIAM and Hong Kong Universities organized…
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Large-time asymptotics in Deep Learning by Borjan Geshkovski

Large-time asymptotics in Deep Learning by Borjan Geshkovski

Tags: deep learning
Last Friday October 23rd our team member Borjan Geshkovski PhD student at DyCon ERC Project from UAM, gave a talk at "Seminario de estadística" organized by the UAM - Universidad…
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Turnpike Control and Deep Learning by Enrique Zuazua at IITK

Turnpike Control and Deep Learning by Enrique Zuazua at IITK

Tags: 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,…
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Turnpike Control and Deep Learning at IITK by E. Zuazua

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

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

Tags: 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…
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Last Publications

Optimal actuator design via Brunovsky’s normal form

Stability and Convergence of a Randomized Model Predictive Control Strategy

Slow decay and Turnpike for Infinite-horizon Hyperbolic LQ problems

Control of certain parabolic models from biology and social sciences

Relaxation approximation and asymptotic stability of stratified solutions to the IPM equation

  • Postdoc at DASEL project -Open position
  • FAU MoD Lecture: Applications of AAA Rational Approximation
  • DASEL
  • Optimal actuator design via Brunovsky’s normal form
  • ERC DyCon Impact Dimension (2016-2022)
  • Postdoc at DASEL project -Open position
  • FAU MoD Lecture: Applications of AAA Rational Approximation
  • DASEL
  • Optimal actuator design via Brunovsky’s normal form
  • ERC DyCon Impact Dimension (2016-2022)
Copyright 2016 - 2023 — . All rights reserved. Chair of Computational Mathematics, Deusto Foundation - University of Deusto
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