A Clash GUI based on tauri. Supports Windows, macOS and Linux.

「Java学习+面试指南」一份涵盖大部分 Java 程序员所需要掌握的核心知识。准备 Java 面试，首选 JavaGuide！

java项目实战练习

Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet…

Unofficial PyTorch Implementation of Unsupervised Data Augmentation.

UDA(Unsupervised Data Augmentation) implemented by pytorch

Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization

Software that can perform photorealistic style transfer without the need of any post-processing steps.

An Incremental Learning, Continual Learning, and Life-Long Learning Repository

A clean and readable Pytorch implementation of CycleGAN

This is an implementation of our paper "HybridRepair: Towards Annotation-Efficient Repair for Deep Learning Models", which will be presented in ISSTA'22.

Code release for "Partial Adversarial Domain Adaptation" (ECCV 2018)

Implementation for the paper "Adversarial Continual Learning" in PyTorch.

中英文敏感词、语言检测、中外手机/电话归属地/运营商查询、名字推断性别、手机号抽取、身份证抽取、邮箱抽取、中日文人名库、中文缩写库、拆字词典、词汇情感值、停用词、反动词表、暴恐词表、繁简体转换、英文模拟中文发音、汪峰歌词生成器、职业名称词库、同义词库、反义词库、否定词库、汽车品牌词库、汽车零件词库、连续英文切割、各种中文词向量、公司名字大全、古诗词库、IT词库、财经词库、成语词库、地名词库、…

CVPR 2021 | Code to reproduce the results of the paper: A Khakzar, S Baselizadeh, S Khanduja, C Rupprecht, ST Kim, N Navab, Neural Response Interpretation through the Lens of Critical Pathways

Start from Interpret Neural Networks by Identifying Critical Data Routing Paths

Code for the NuerIPS'19 paper "Gate Decorator: Global Filter Pruning Method for Accelerating Deep Convolutional Neural Networks"

Load Caffe networks in Torch7

标注自己的数据集，训练、评估、测试、部署自己的人工智能算法

Code for the Proceedings of the National Academy of Sciences 2020 article, "Understanding the Role of Individual Units in a Deep Neural Network"

AI-Lancet, backdoor removal

Learning Efficient Convolutional Networks through Network Slimming, In ICCV 2017.

code for "Training Interpretable Convolutional NeuralNetworks by Differentiating Class-specific Filters"

A Self-Consistent Robust Error (ICML 2022)

复现了下Neural Cleanse这篇论文，真的是简单而有效，发在了okaland

The Charon tool for analyzing neural network robustness

This is a curated list for Information Bottleneck Principle, in memory of Professor Naftali Tishby.

This repo keeps track of popular provable training and verification approaches towards robust neural networks, including leaderboards on popular datasets and paper categorization.