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There is a page named "Neural operators" on Wikipedia

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  • Neural operators are a class of deep learning architectures designed to learn maps between infinite-dimensional function spaces. Neural operators represent...
    15 KB (2,039 words) - 01:06, 29 March 2024
  • Thumbnail for Neural network (machine learning)
    In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a model inspired by the structure and function...
    164 KB (17,405 words) - 20:49, 30 July 2024
  • Thumbnail for Miroslav Krstić
    ". Bhan, Shi, Krstic, Neural Operators for Bypassing Gain and Control Computations in PDE Backstepping (2023). "Neural Operators for Bypassing Gain and...
    55 KB (5,181 words) - 17:37, 14 July 2024
  • discovery, scientific simulations and engineering design. She invented Neural Operators that extend deep learning to modeling multi-scale processes in these...
    26 KB (2,336 words) - 03:34, 22 April 2024
  • A convolutional neural network (CNN) is a regularized type of feed-forward neural network that learns features by itself via filter (or kernel) optimization...
    134 KB (15,089 words) - 06:28, 26 July 2024
  • The Open Neural Network Exchange (ONNX) [ˈɒnɪks] is an open-source artificial intelligence ecosystem of technology companies and research organizations...
    6 KB (471 words) - 18:24, 27 April 2024
  • Thumbnail for Quantum neural network
    the sample model neural network above. Since the Quantum neural network being discussed uses fan-out Unitary operators, and each operator only acts on its...
    21 KB (2,542 words) - 11:51, 25 May 2024
  • Thumbnail for Physics-informed neural networks
    Physics-informed neural networks (PINNs), also referred to as Theory-Trained Neural Networks (TTNs), are a type of universal function approximators that...
    30 KB (3,760 words) - 08:31, 26 July 2024
  • Thumbnail for Deep learning
    Deep learning is the subset of machine learning methods based on neural networks with representation learning. The adjective "deep" refers to the use of...
    179 KB (17,806 words) - 06:57, 3 August 2024
  • A graph neural network (GNN) belongs to a class of artificial neural networks for processing data that can be represented as graphs. In the more general...
    35 KB (3,972 words) - 04:47, 19 June 2024
  • Artificial neural networks (ANNs) are models created using machine learning to perform a number of tasks. Their creation was inspired by neural circuitry...
    62 KB (6,433 words) - 14:24, 2 July 2024
  • An AI accelerator, deep learning processor or neural processing unit (NPU) is a class of specialized hardware accelerator or computer system designed to...
    49 KB (4,765 words) - 13:13, 3 August 2024
  • Thumbnail for Neural tube defect
    Neural tube defects (NTDs) are a group of birth defects in which an opening in the spine or cranium remains from early in human development. In the third...
    50 KB (5,814 words) - 12:37, 7 June 2024
  • Brain implant (redirect from Neural implant)
    Brain implants, often referred to as neural implants, are technological devices that connect directly to a biological subject's brain – usually placed...
    58 KB (6,356 words) - 03:14, 31 July 2024
  • have built devices to interface with neural cells and entire neural networks in vitro. Experiments on cultured neural tissue focused on building problem-solving...
    145 KB (16,862 words) - 16:09, 30 July 2024
  • Perceptron (category Artificial neural networks)
    This caused the field of neural network research to stagnate for many years, before it was recognised that a feedforward neural network with two or more...
    45 KB (5,871 words) - 04:37, 31 July 2024
  • Thumbnail for Stochastic Neural Analog Reinforcement Calculator
    The Stochastic Neural Analog Reinforcement Calculator (SNARC) is a neural-net machine designed by Marvin Lee Minsky. Prompted by a letter from Minsky,...
    7 KB (740 words) - 09:51, 27 July 2024
  • Thumbnail for Long short-term memory
    Long short-term memory (category Neural network architectures)
    Long short-term memory (LSTM) is a type of recurrent neural network (RNN) aimed at dealing with the vanishing gradient problem present in traditional RNNs...
    53 KB (5,895 words) - 13:54, 20 July 2024
  • Thumbnail for Convolution
    with the translation operators. Consider the family S of operators consisting of all such convolutions and the translation operators. Then S is a commuting...
    66 KB (8,694 words) - 06:04, 28 July 2024
  • Fuzzy logic (redirect from Zadeh operator)
    for basic operators ("gates") AND, OR, NOT must be available. There are several ways to this. A common replacement is called the Zadeh operators: For TRUE/1...
    55 KB (6,688 words) - 12:56, 25 July 2024
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