Min's Projects
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
Official PyTorch implementation of "Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup" (ICML'20)
Papers with code. Sorted by stars. Updated weekly.
Codebase for Image Classification Research, written in PyTorch.
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)
PyGraphistry is a library to extract, transform, and visually explore big graphs
A Python Library for Health Predictive Models
A Python wrapper around Metis, a graph partitioning package
(JMLR'19) A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)
A library for encrypted, privacy preserving deep learning
Louvain Community Detection
python client library for interacting with Project Vote Smart API
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Generate embeddings from large-scale graph-structured data.
95.16% on CIFAR10 with PyTorch
Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet, WideResNet)
Training PyTorch models with differential privacy
PyTorch implementations of Generative Adversarial Networks.
Representation learning on large graphs using stochastic graph convolutions.
pytorch handbook是一本开源的书籍,目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门,其中包含的Pytorch教程全部通过测试保证可以成功运行
Implementation of https://arxiv.org/abs/1904.00962
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch
Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)
simple Differential Privacy in PyTorch
Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText. [IN PROGRESS]