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python-cg-implementation

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conjugate-gradient-sparse-cg-solver-course

SENATOROVAI / conjugate-gradient-sparse-cg-solver-course

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The Conjugate Gradient (CG) method is an efficient iterative algorithm for solving large, sparse systems of linear equations where the matrix is symmetric and positive-definite. It finds the minimum of a quadratic function by generating conjugate search directions, ensuring convergence in at most steps for an matrix.Solver

python optimization solver scientific-computing iterative-methods conjugate-gradient sparse-linear-solver numerical-linear-algebra matrix-algorithms preconditioned-conjugate-gradient large-scale-optimization optimization-solver senatorov preconditioned-cg python-cg-implementation iterative-solver sparse-cg-solver solver-sparse-cg
  • Updated Mar 17, 2026
  • Jupyter Notebook

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