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Related lectures (26)
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Asymptotic States and S-matrix
Covers the concept of asymptotic states and S-matrix in quantum field theory, focusing on the evolution of wave packets and the scattering states.
QR Factorization: Least Squares System Resolution
MOOC: Linear Algebra (Part 3)
Covers the QR factorization method applied to solving a system of linear equations in the least squares sense.
Asymptotic States and S-matrix: Operators
Explores asymptotic states, S-matrix, and operators in quantum field theory, emphasizing the role of discrete symmetries and complete sets of states.
Asymptotic States and S-matrix
Explores asymptotic states, S-matrix, Lippmann-Schwinger equation, and energy robustness in quantum field theory.
Discrete Symmetries: Asymptotic States and S-matrix
Covers the concept of discrete symmetries, focusing on the introduction to asymptotic states and S-matrix.
SVD: Singular Value Decomposition
Covers the concept of Singular Value Decomposition (SVD) for compressing information in matrices and images.
Linear Systems Resolution
MOOC: Linear Algebra (Part 1)
Explores LU decomposition for solving linear systems and the associativity of operations.
Linear Algebra Review
Covers the basics of linear algebra, including matrix operations and singular value decomposition.
Matrix Form and IO Analysis
Covers Material Flow Analysis in matrix form and Input-Output Analysis, exploring balance equations, transfer coefficients, GHG emissions, and economic impact.
Density Operator: Quantum Physics II
Covers the concept of matrix to the density operator in quantum physics.
Direct Methods for Linear Systems of Equations
Explores direct methods for solving linear systems of equations, including Gauss elimination and LU decomposition.
Latent Factor Analysis: Movie Genre Classification
Explores latent factor analysis for movie genre classification based on male versus female leads.
QR Factorization: Orthogonal Bases
MOOC: Linear Algebra (Part 3)
Covers the QR factorization of a matrix A into Q and R.
Cholesky Factorization: Theory and Algorithm
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Explores the Cholesky factorization method for symmetric positive definite matrices.
Linear Systems: Direct Methods
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Covers the formulation of linear systems, direct and iterative methods for solving them, and the cost of LU factorization.
Matrix Factorization: LU Decomposition
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Covers the LU decomposition method for matrix factorization and its application in electrical engineering.
Matrix Factorization: LU Decomposition
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Explores LU decomposition for matrix factorization and solving linear systems.
Matrix Factorizations: LU Decomposition
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Introduces LU decomposition for efficient linear equation solving using matrix factorization.
Spectral Decomposition
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Explores spectral and singular value decompositions of matrices.
Numerical Analysis: Direct Methods for Linear Systems
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Covers direct methods for solving linear systems in numerical analysis.
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