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  2. Laplacian matrix - Wikipedia

    en.wikipedia.org/wiki/Laplacian_matrix

    A vertex with a large degree, also called a heavy node, results in a large diagonal entry in the Laplacian matrix dominating the matrix properties. Normalization is aimed to make the influence of such vertices more equal to that of other vertices, by dividing the entries of the Laplacian matrix by the vertex degrees.

  3. Degree matrix - Wikipedia

    en.wikipedia.org/wiki/Degree_matrix

    In the mathematical field of algebraic graph theory, the degree matrix of an undirected graph is a diagonal matrix which contains information about the degree of each vertex—that is, the number of edges attached to each vertex. [1]

  4. Relaxation (iterative method) - Wikipedia

    en.wikipedia.org/wiki/Relaxation_(iterative_method)

    Relaxation methods are used to solve the linear equations resulting from a discretization of the differential equation, for example by finite differences. [ 2 ] [ 3 ] [ 4 ] Iterative relaxation of solutions is commonly dubbed smoothing because with certain equations, such as Laplace's equation , it resembles repeated application of a local ...

  5. Calculus on finite weighted graphs - Wikipedia

    en.wikipedia.org/wiki/Calculus_on_finite...

    The continuous -Laplace operator is a second-order differential operator that can be well-translated to finite weighted graphs. It allows the translation of various partial differential equations, e.g., the heat equation, to the graph setting.

  6. Discrete Laplace operator - Wikipedia

    en.wikipedia.org/wiki/Discrete_Laplace_operator

    Notice that this equation takes the same form as the heat equation, where the matrix −L is replacing the Laplacian operator ; hence, the "graph Laplacian". To find a solution to this differential equation, apply standard techniques for solving a first-order matrix differential equation.

  7. Proto-value function - Wikipedia

    en.wikipedia.org/wiki/Proto-value_function

    They provide a novel framework for solving the credit assignment problem. The framework introduces a novel approach to solving Markov decision processes (MDP) and reinforcement learning problems, using multiscale spectral and manifold learning methods. Proto-value functions are generated by spectral analysis of a graph, using the graph Laplacian.

  8. Gauss–Seidel method - Wikipedia

    en.wikipedia.org/wiki/Gauss–Seidel_method

    In numerical linear algebra, the Gauss–Seidel method, also known as the Liebmann method or the method of successive displacement, is an iterative method used to solve a system of linear equations. It is named after the German mathematicians Carl Friedrich Gauss and Philipp Ludwig von Seidel .

  9. Nine-point stencil - Wikipedia

    en.wikipedia.org/wiki/Nine-point_stencil

    On the other hand, if controlled anisotropic effects are a desired feature, when solving anisotropic diffusion problems for example, it is also possible to use the 9-point stencil combined with tensors to generate them. Consider the laplacian in the following form: =