Description:

Operator Discretization Library (ODL) is a Python library that enables research in inverse problems on realistic or real data. The framework allows to encapsulate a physical model into an Operator that can be used like a mathematical object in, e.g., optimization methods. Furthermore, ODL makes it easy to experiment with reconstruction methods and optimization algorithms for variational regularization, all without sacrificing performance.

Changes to previous version:

Initial Announcement on mloss.org.

BibTeX Entry: Download

Supported Operating Systems: Linux, Windows, Osx

Data Formats: Agnostic

Tags: Inverse Problems, Mathematics

Archive: download here

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