Hybrid methods refer to computational techniques that combine different algorithms or strategies to improve the solution of inverse problems. These methods often leverage the strengths of various approaches, such as regularization techniques and optimization algorithms, to effectively handle ill-posed problems. By blending these methods, hybrid approaches can enhance convergence properties and stabilize solutions while also making the computation more efficient.
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