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  2. Residual neural network - Wikipedia

    en.wikipedia.org/wiki/Residual_neural_network

    A residual neural network (also referred to as a residual network or ResNet) [1] is a deep learning architecture in which the layers learn residual functions with reference to the layer inputs. It was developed in 2015 for image recognition , and won the ImageNet Large Scale Visual Recognition Challenge ( ILSVRC ) of that year.

  3. AlexNet - Wikipedia

    en.wikipedia.org/wiki/AlexNet

    If one freezes the rest of the model and only finetune the last layer, one can obtain another vision model at cost much less than training one from scratch. AlexNet block diagram AlexNet is a convolutional neural network (CNN) architecture, designed by Alex Krizhevsky in collaboration with Ilya Sutskever and Geoffrey Hinton , who was Krizhevsky ...

  4. PyTorch - Wikipedia

    en.wikipedia.org/wiki/PyTorch

    In September 2022, Meta announced that PyTorch would be governed by the independent PyTorch Foundation, a newly created subsidiary of the Linux Foundation. [ 24 ] PyTorch 2.0 was released on 15 March 2023, introducing TorchDynamo , a Python-level compiler that makes code run up to 2x faster, along with significant improvements in training and ...

  5. PyTorch Lightning - Wikipedia

    en.wikipedia.org/wiki/PyTorch_Lightning

    PyTorch Lightning is an open-source Python library that provides a high-level interface for PyTorch, a popular deep learning framework. [1] It is a lightweight and high-performance framework that organizes PyTorch code to decouple research from engineering, thus making deep learning experiments easier to read and reproduce.

  6. U-Net - Wikipedia

    en.wikipedia.org/wiki/U-Net

    U-Net is a convolutional neural network that was developed for image segmentation. [1] The network is based on a fully convolutional neural network [2] whose architecture was modified and extended to work with fewer training images and to yield more precise segmentation.

  7. bfloat16 floating-point format - Wikipedia

    en.wikipedia.org/wiki/Bfloat16_floating-point_format

    Many libraries support bfloat16, such as CUDA, [13] Intel oneAPI Math Kernel Library, AMD ROCm, [14] AMD Optimizing CPU Libraries, PyTorch, and TensorFlow. [ 10 ] [ 15 ] On these platforms, bfloat16 may also be used in mixed-precision arithmetic , where bfloat16 numbers may be operated on and expanded to wider data types.