pytorch-loss
Loss functions
Provides a comprehensive set of implementation of various loss functions and operators for deep learning models
label-smooth, amsoftmax, partial-fc, focal-loss, triplet-loss, lovasz-softmax. Maybe useful
2k stars
23 watching
373 forks
Language: Python
last commit: about 1 month ago amsoftmaxcudadice-lossemafocal-losslabel-smoothinglovasz-softmaxmishpartial-fcpytorchtriplet-loss
Related projects:
Repository | Description | Stars |
---|---|---|
hanxunh/active-passive-losses | A PyTorch-based framework for implementing normalized loss functions to improve deep learning model robustness against noisy labels. | 134 |
alanchou/truncated-loss | An implementation of a loss function designed to improve the training of deep neural networks with noisy labels | 125 |
mblondel/fenchel-young-losses | Provides Fenchel-Young losses for probabilistic classification in PyTorch/TensorFlow/scikit-learn. | 183 |
bes-dev/mpl.pytorch | A PyTorch implementation of a loss function used in semantic image segmentation | 175 |
kefirski/pytorch_neg_loss | A PyTorch implementation of negative sampling loss for text classification models | 125 |
rachtsingh/lgamma | Implementations of mathematical special functions for use in machine learning and PyTorch applications | 24 |
chosj95/mimo-unet | Develops a deep learning model for single image deblurring with improved performance and computational efficiency | 373 |
kaiyangzhou/dassl.pytorch | A PyTorch toolbox for supporting research and development of domain adaptation, generalization, and semi-supervised learning methods in computer vision. | 1,217 |
pochih/fcn-pytorch | A Python implementation of fully convolutional networks for semantic segmentation in computer vision. | 406 |
zhanghang1989/pytorch-encoding | A Python framework for building deep learning models with optimized encoding layers and batch normalization. | 2,041 |
seannaren/warp-ctc | PyTorch bindings for the Warp-CTC loss function used in speech recognition. | 757 |
unsky/focal-loss | An implementation of the focal loss algorithm for dense object detection in deep learning models. | 485 |
yunlongdong/fcn-pytorch | A PyTorch implementation of FCN for semantic segmentation with an easy-to-use interface and pre-trained models. | 160 |
zudi-lin/pytorch_connectomics | A deep learning framework for automatic and semi-automatic segmentation of 3D image stacks in connectomics | 171 |
zapata-engineering/orqviz | Visualizes loss landscapes of parameterized quantum algorithms | 86 |