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  2. Torch (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Torch_(machine_learning)

    The core package of Torch is torch. It provides a flexible N-dimensional array or Tensor, which supports basic routines for indexing, slicing, transposing, type-casting, resizing, sharing storage and cloning. This object is used by most other packages and thus forms the core object of the library.

  3. PyTorch - Wikipedia

    en.wikipedia.org/wiki/PyTorch

    PyTorch is a machine learning library based on the Torch library, [4] [5] [6] used for applications such as computer vision and natural language processing, [7] originally developed by Meta AI and now part of the Linux Foundation umbrella.

  4. Row- and column-major order - Wikipedia

    en.wikipedia.org/wiki/Row-_and_column-major_order

    Note how the use of A[i][j] with multi-step indexing as in C, as opposed to a neutral notation like A(i,j) as in Fortran, almost inevitably implies row-major order for syntactic reasons, so to speak, because it can be rewritten as (A[i])[j], and the A[i] row part can even be assigned to an intermediate variable that is then indexed in a separate expression.

  5. SymbolicC++ - Wikipedia

    en.wikipedia.org/wiki/SymbolicC++

    SymbolicC++ is a general purpose computer algebra system written in the programming language C++. It is free software released under the terms of the GNU General Public License. SymbolicC++ is used by including a C++ header file or by linking against a library.

  6. Method (computer programming) - Wikipedia

    en.wikipedia.org/wiki/Method_(computer_programming)

    Perhaps the most well-known example is C++, an object-oriented extension of the C programming language. Due to the design requirements to add the object-oriented paradigm on to an existing procedural language, message passing in C++ has some unique capabilities and terminologies. For example, in C++ a method is known as a member function.

  7. Physics-informed neural networks - Wikipedia

    en.wikipedia.org/wiki/Physics-informed_neural...

    Physics-informed neural networks for solving Navier–Stokes equations. Physics-informed neural networks (PINNs), [1] also referred to as Theory-Trained Neural Networks (TTNs), [2] are a type of universal function approximators that can embed the knowledge of any physical laws that govern a given data-set in the learning process, and can be described by partial differential equations (PDEs).

  8. Object-oriented programming - Wikipedia

    en.wikipedia.org/wiki/Object-oriented_programming

    Objects can contain other objects in their instance variables; this is known as object composition. For example, an object in the Employee class might contain (either directly or through a pointer) an object in the Address class, in addition to its own instance variables like "first_name" and "position".

  9. List of object-oriented programming languages - Wikipedia

    en.wikipedia.org/wiki/List_of_object-oriented...

    This is a list of notable programming languages with features designed for object-oriented programming (OOP). The listed languages are designed with varying degrees of OOP support. Some are highly focused in OOP while others support multiple paradigms including OOP.