Produce and understand the definitions of vector space, subspace, linear independence of vectors, bases of vector spaces, the dimension of a vector space. • Apply facts about these notions in ...

This course gives a thorough introduction to linear algebra with emphasis on vector spaces, linear maps, spectral theory, orthogonality and applications of this theory. MATLAB is used for ...

This undergraduate textbook on Linear Algebra and n-Dimensional Geometry ... The explanations in this book are detailed, lucid, and supported with numerous well-constructed examples to capture the ...

Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math ...

Matrix algebra and Gaussian elimination. The geometry of vectors in R2, R3 and Rn. Vector spaces and linear transformation. Introduction to orthogonal geometry and eigenvalue problems. Meets the ...

As most of the computation time is spent in the linear solver, and because problem scalability ... I develop a family of solvers based upon a technique known as "Krylov Subspace Recycling". The Belos ...

Among other things, the course includes elementary linear algebra, the solution of equation systems ... analyze such models in your own academic work, for example in analyses that are part of the ...

In the past decade, a series of remarkable solutions to long-standing problems in C *-algebra using set-theoretic methods, many achieved by the author and his collaborators, have generated new ...

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Institute of Physics, Faculty of Physics, Astronomy and Informatics, Nicolaus Copernicus University in Toruń, Grudziadzka 5/7, 87-100 Toruń, Poland ...