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  2. Neural radiance field - Wikipedia

    en.wikipedia.org/wiki/Neural_radiance_field

    Neural radiance field. A neural radiance field (NeRF) is a method based on deep learning for reconstructing a three-dimensional representation of a scene from two-dimensional images. The NeRF model enables downstream applications of novel view synthesis, scene geometry reconstruction, and obtaining the reflectance properties of the scene.

  3. Light field - Wikipedia

    en.wikipedia.org/wiki/Light_field

    A light field, or lightfield, is a vector function that describes the amount of light flowing in every direction through every point in a space. The space of all possible light rays is given by the five-dimensional plenoptic function, and the magnitude of each ray is given by its radiance. Michael Faraday was the first to propose that light ...

  4. 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).

  5. Deep learning - Wikipedia

    en.wikipedia.org/wiki/Deep_learning

    Deep learning is a subset of machine learning methods based on neural networks with representation learning.The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.

  6. Neural modeling fields - Wikipedia

    en.wikipedia.org/wiki/Neural_modeling_fields

    Neural modeling field (NMF) is a mathematical framework for machine learning which combines ideas from neural networks, fuzzy logic, and model based recognition. It has also been referred to as modeling fields, modeling fields theory (MFT), Maximum likelihood artificial neural networks (MLANS). [1][2][3][4] [5][6] This framework has been ...

  7. Gaussian splatting - Wikipedia

    en.wikipedia.org/wiki/Gaussian_splatting

    Gaussian splatting is a volume rendering technique that deals with the direct rendering of volume data without converting the data into surface or line primitives. [1] The technique was originally introduced as splatting by Lee Westover in the early 1990s. [2] With advancements in computer graphics, newer methods such as 3D and 4D Gaussian ...

  8. Reinforcement learning from human feedback - Wikipedia

    en.wikipedia.org/wiki/Reinforcement_learning...

    e. In machine learning, reinforcement learning from human feedback (RLHF) is a technique to align an intelligent agent with human preferences. It involves training a reward model to represent preferences, which can then be used to train other models through reinforcement learning. In classical reinforcement learning, an intelligent agent's goal ...

  9. Rendering (computer graphics) - Wikipedia

    en.wikipedia.org/wiki/Rendering_(computer_graphics)

    Rendering or image synthesis is the process of generating a photorealistic or non-photorealistic image from a 2D or 3D model by means of a computer program. [citation needed] The resulting image is referred to as a rendering. Multiple models can be defined in a scene file containing objects in a strictly defined language or data structure.