Systems, Patterns and Data Engineering with Geometric Calculi

Inbunden, Engelska, 2021

Av Sebastià Xambó-Descamps, Sebastia Xambo-Descamps, Sebastià

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The intention of this collection agrees with the purposes of the homonymous mini-symposium (MS) at ICIAM-2019, which were to overview the essentials of geometric calculus (GC) formalism, to report on state-of-the-art applications showcasing its advantages and to explore the bearing of GC in novel approaches to deep learning.

Produktinformation

Utgivningsdatum2021-07-17
Mått155 x 235 x 17 mm
Vikt459 g
FormatInbunden
SpråkEngelska
SerieSEMA SIMAI Springer Series
Antal sidor179
FörlagSpringer Nature Switzerland AG
ISBN9783030744854

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Sebastià Xambó-Descamps is an Emeritus Full Professor of Mathematics at the Universitat Politècnica de Catalunya/Barcelonatech and is currently visiting the Barcelona Supercomputer Center. Previously, he held positions at the Universidad Complutense de Madrid (Full Professor) and at the Universitat de Barcelona (Associate Professor). His main research interests are algebraic geometry (intersection theory and enumerative geometry), information theory (coding theory and code-based post-quantum cryptography), computational methods (computer mathematics and symbolic computation), mathematical models in physics and engineering, geometric calculus and its applications to deep learning. Author of Block Error-Correcting Codes, A Computational Primer and Real Spinorial Groups, A Short Mathematical Introduction.

1 I. Zaplana, New Perspectives on Robotics with Geometric Calculus.- 2 C. Lavor and R. Alves, Recent advances on oriented conformal geometric algebra applied to molecular distance geometry.- 3 S. Franchini and S. Vitabile, Geometric Calculus Applications to Medical Imaging: Status and Perspectives.- 4 L. Dorst, Optimal Combination of Orientation Measurements Under Angle, Axis and Chord Metrics.- 5 P. Colapinto, Space-Bending Lattices through Conformal Transformation of Principal Contact Elements .- 6 L. A. F. Fernandes, Exploring Lazy Evaluation and Compile-Time Simplifications for Efficient Geometric Algebra Computations.- 7 E. U. Moya-Sánchez et al., A Quaternion Deterministic Monogenic CNN Layer for Contrast Invariance.- 8 S. Xambó-Descamps et al., Geometric Calculi and Automatic Learning: An Overview.