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  2. 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).

  3. Machine learning in physics - Wikipedia

    en.wikipedia.org/wiki/Machine_learning_in_physics

    A deep learning system was reported to learn intuitive physics from visual data (of virtual 3D environments) based on an unpublished approach inspired by studies of visual cognition in infants. [ 40 ] [ 39 ] Other researchers have developed a machine learning algorithm that could discover sets of basic variables of various physical systems and ...

  4. AdS/CFT correspondence - Wikipedia

    en.wikipedia.org/wiki/AdS/CFT_correspondence

    In a letter to Physics Today, Nobel laureate Philip W. Anderson voiced similar concerns about applications of AdS/CFT to condensed matter physics, stating As a very general problem with the AdS/CFT approach in condensed-matter theory, we can point to those telltale initials "CFT"—conformal field theory.

  5. Digital signal processing - Wikipedia

    en.wikipedia.org/wiki/Digital_signal_processing

    Digital signal processing (DSP) is the use of digital processing, such as by computers or more specialized digital signal processors, to perform a wide variety of signal processing operations. The digital signals processed in this manner are a sequence of numbers that represent samples of a continuous variable in a domain such as time, space ...

  6. AI accelerator - Wikipedia

    en.wikipedia.org/wiki/AI_accelerator

    An AI accelerator, deep learning processor or neural processing unit (NPU) is a class of specialized hardware accelerator [1] or computer system [2] [3] designed to accelerate artificial intelligence (AI) and machine learning applications, including artificial neural networks and computer vision.

  7. Levels of Processing model - Wikipedia

    en.wikipedia.org/wiki/Levels_of_Processing_model

    Conversely, deep processing (e.g., semantic processing) results in a more durable memory trace. [1] There are three levels of processing in this model. Structural processing, or visual, is when we remember only the physical quality of the word (e.g. how the word is spelled and how letters look).

  8. Physics engine - Wikipedia

    en.wikipedia.org/wiki/Physics_engine

    A physics processing unit (PPU) is a dedicated microprocessor designed to handle the calculations of physics, especially in the physics engine of video games. Examples of calculations involving a PPU might include rigid body dynamics , soft body dynamics , collision detection , fluid dynamics , hair and clothing simulation, finite element ...

  9. Artificial life - Wikipedia

    en.wikipedia.org/wiki/Artificial_life

    Artificial life (ALife or A-Life) is a field of study wherein researchers examine systems related to natural life, its processes, and its evolution, through the use of simulations with computer models, robotics, and biochemistry. [1]