Min's Projects
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]
Siamese Network implementation using Pytorch
pytorch structural similarity (SSIM) loss
pytorch-tiny-imagenet
Build your neural network easy and fast
This is the PyTorch implementation of VGG network trained on CIFAR10 dataset
Pretrained TorchVision models on CIFAR10 dataset (with weights)
PyTorch Extension Library of Optimized Graph Cluster Algorithms
Convolutional Gated Recurrent Units implemented in PyTorch
Geometric Deep Learning Extension Library for PyTorch
Code for CVPR2020 paper QEBA: Query-Efficient Boundary-Based Blackbox Attack
This technique modifies image data so that any model trained on it will bear an identifiable mark.
Learning operating system development using Linux kernel and Raspberry Pi
Toolkit developed to reverse engineer Google's Nearby Connections API
A simple tool in Python to fix incorrect bib entries automatically, based on their official information from the full ACL anthology and DBLP (for ICLR and other conferences)!
A list of compatible datasets, noting other major repositories containing popular real-world datasets, along with sample code for a range of recommendation tasks.
This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.
Source code for paper: Regression Model Fitting under Differential Privacy and Model Inversion Attack
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
Meta repository with getting-started info for projects released by Abstract group at CMU
[ICLR 2020] Contrastive Representation Distillation (CRD), and benchmark of recent knowledge distillation methods
Research at Protocol Labs