SJTUzhanglj's starred repositories
PlotNeuralNet
Latex code for making neural networks diagrams
pytorch-OpCounter
Count the MACs / FLOPs of your PyTorch model.
box-convolutions
PyTorch code for the "Deep Neural Networks with Box Convolutions" paper
AutoAugment
Unofficial implementation of the ImageNet, CIFAR 10 and SVHN Augmentation Policies learned by AutoAugment using pillow
dataset-distillation
Dataset Distillation
equivariant-transformers
Equivariant Transformer (ET) layers are image-to-image mappings that incorporate prior knowledge on invariances with respect to continuous transformations groups (ICML 2019). Paper: https://arxiv.org/abs/1901.11399
cs-ranking
Context-sensitive ranking and choice in Python with PyTorch
pre-training
Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)
awesome-self-supervised-learning
A curated list of awesome self-supervised methods
entropy-sgd
Lua implementation of Entropy-SGD
nsfw_data_scraper
Collection of scripts to aggregate image data for the purposes of training an NSFW Image Classifier
visual-attribution
Pytorch Implementation of recent visual attribution methods for model interpretability
NetDissect-Lite
Light version of Network Dissection for Quantifying Interpretability of Networks
multiple-objects-gan
Implementation for "Generating Multiple Objects at Spatially Distinct Locations" (ICLR 2019)
Matrix-Capsules-pytorch
A Pytorch implementation of "Matrix Capsules with EM routing"
awesome-capsule-networks
A curated list of awesome resources related to capsule networks
capsule-networks
A PyTorch implementation of the NIPS 2017 paper "Dynamic Routing Between Capsules".
YOLO_v3_tutorial_from_scratch
Accompanying code for Paperspace tutorial series "How to Implement YOLO v3 Object Detector from Scratch"
DeepLearning-500-questions
深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为18个章节,50余万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系scutjy2015@163.com 版权所有,违权必究 Tan 2018.06
transferlearning
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习