by Kurusch Ebrahimi-Fard, Hans Munthe-Kaas and Cordian Riener For much of the twentieth century, mathematics evolved along two largely separate trajectories.On one side stood abstraction:
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Trondheim. Patterns from instability: How 1D soliton breaks dimensions to find 2D surfaces
By Wei Lian NTNU Norwegian University of Science and Technology In engineering, “instability” is often viewed as a failure—a bridge buckling in the wind or
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Trondheim. Learning Differential Equations via Chen–Fliess series
This article presents an accessible overview of how Chen–Fliess series can be combined with modern learning techniques to model and analyze nonlinear dynamical systems. The
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Trondheim. Affinization of Reduced Basis Methods
by Trond Kvamsdal NTNU Norwegian University of Science and Technology Background Reduced-basis methods (RBMs) offer an efficient framework for computing real-time approximations of parameterized PDEs.
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Trondheim. DidactiQC — Teaching Quantum Computing in Norway
By Kurusch Ebrahimi Fard, Yael Fleischmann, and Alexander Schmeding NTNU Norwegian University of Science and Technology Why the Mathematics of Quantum Computing Matters Quantum computing
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Trondheim. Geometry and Numerical Analysis of Control Systems
by Jacob Goodman NTNU Norwegian University of Science and Technology Modern engineering systems are expected to operate in environments that are complex, uncertain, and full
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Trondheim. Rediscovering shallow‑water soliton equations from video data
By Mats Ehrnström NTNU Norwegian University of Science and Technology Can we rediscover a classical PDE from crude experimental data — just video recordings of
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Trondheim. DIScover — discovering dynamics from data, with uncertainty built in
By Mats Ehrnström NTNU Norwegian University of Science and Technology DIScover is a collaboration and centre proposal in mathematical sciences designed to make dynamical discovery
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Coimbra. Hybrid Algorithms: Surpassing the Complexity and Challenges of Real-World Problems.
In the dynamic landscape of real-world problem-solving, the challenges have reached unprecedented levels of complexity. Addressing these intricate issues demands intelligent models and algorithms that
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Coimbra. iMath Project and MathE Platform Personalize Learning, Making it Accessible and Engaging
Students exhibit diverse learning styles, ranging from logical to musical, and naturalist, among others. Consequently, the conventional lecturer-centered or passive teaching approach may not suit
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