FrankWJW's Stars
facebookresearch/segment-anything
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
HarisIqbal88/PlotNeuralNet
Latex code for making neural networks diagrams
dair-ai/ml-visuals
🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
mlfoundations/open_clip
An open source implementation of CLIP.
qubvel-org/segmentation_models.pytorch
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
aladdinpersson/Machine-Learning-Collection
A resource for learning about Machine learning & Deep Learning
kuangliu/pytorch-cifar
95.47% on CIFAR10 with PyTorch
Lyken17/pytorch-OpCounter
Count the MACs / FLOPs of your PyTorch model.
MLNLP-World/Paper-Writing-Tips
MLNLP社区用来帮助大家避免论文投稿小错误的整理仓库。 Paper Writing Tips
bethgelab/foolbox
A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX
Harry24k/adversarial-attacks-pytorch
PyTorch implementation of adversarial attacks [torchattacks]
jakesnell/prototypical-networks
Code for the NeurIPS 2017 Paper "Prototypical Networks for Few-shot Learning"
MIC-DKFZ/batchgenerators
A framework for data augmentation for 2D and 3D image classification and segmentation
google/svcca
Jingkang50/OODSurvey
The Official Repository for "Generalized OOD Detection: A Survey"
WangYueFt/rfs
HzFu/COVID19_imaging_AI_paper_list
COVID-19 imaging-based AI paper collection
gitabcworld/MatchingNetworks
This repo provides pytorch code which replicates the results of the Matching Networks for One Shot Learning paper on the Omniglot and MiniImageNet dataset
yoyololicon/pytorch-NMF
A pytorch package for non-negative matrix factorization.
IBM/cdfsl-benchmark
(ECCV 2020) Cross-Domain Few-Shot Learning Benchmarking System
Peterisfar/YOLOV3
yolov3 by pytorch
linusericsson/ssl-transfer
Official code for the CVPR 2021 paper "How Well Do Self-Supervised Models Transfer?"
GuyHacohen/curriculum_learning
Code implementing the experiments described in the paper "On The Power of Curriculum Learning in Training Deep Networks" by Hacohen & Weinshall (ICML 2019)
blackfeather-wang/InfoPro-Pytorch
Learning recognition/segmentation models without end-to-end training. 40%-60% less GPU memory footprint. Same training time. Better performance.
chrysts/dsn_fewshot
vkakerbeck/Progressively-Growing-Networks
Experiments on different dataset on how to grow networks during training to learn new image categories.
kamenbliznashki/chexpert
CheXpert competition models -- attention augmented convolutions on DenseNet, ResNet; EfficientNet
guoshengcv/CurriculumNet
CurriculumNet: Weakly Supervised Learning from Large-Scale Web Images
biomedia-mira/chexploration
Official repository for 'Algorithmic encoding of protected characteristics in chest X-ray disease detection models'
piratehao/Local-to-Global-Learning-for-DNNs
Implementation of Local-to-Global-Learning-for-DNNs