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JAVA进阶相关书籍：《JAVA并发编程实践》、《Linux Shell脚本攻略》、《spring揭秘 精选版》、《高性能Mysql》、《深入理解Java虚拟机[JVM高级特性与最佳实践](周志明)》、《图解HTTP 彩色版》、《图解TCP_IP_第5版》、《head+first+servlets jsp》、《How Tomcat Works 中文版》、《J2EE核心模式》、《JAVA并发编…
This is the reading list mainly on adversarial examples (attacks, defenses, etc.) I try to keep and update regularly.
Detecting Adversarial Examples in Deep Neural Networks
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
『Java八股文』Java面试套路，Java进阶学习，打破内卷拿大厂Offer，升职加薪！
deeplearning.ai（吴恩达老师的深度学习课程笔记及资源）
2023年最新总结，阿里，腾讯，百度，美团，头条等技术面试题目，以及答案，专家出题人分析汇总。
📚 C/C++ 技术面试基础知识总结，包括语言、程序库、数据结构、算法、系统、网络、链接装载库等知识及面试经验、招聘、内推等信息。This repository is a summary of the basic knowledge of recruiting job seekers and beginners in the direction of C/C++ technology, in…
Reverse Cross Entropy for Adversarial Detection (NeurIPS 2018)
Image-to-Image Translation in PyTorch
Code for "Detecting Adversarial Samples from Artifacts" (Feinman et al., 2017)
The LLVM Project is a collection of modular and reusable compiler and toolchain technologies.
LevelDB is a fast key-value storage library written at Google that provides an ordered mapping from string keys to string values.
Protocol Buffers - Google's data interchange format
A curated list of awesome C++ (or C) frameworks, libraries, resources, and shiny things. Inspired by awesome-... stuff.
Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)
The Ultimate Reference for Out of Distribution Detection with Deep Neural Networks
A curated list of awesome resources for adversarial examples in deep learning
LeetCode Solutions: A Record of My Problem Solving Journey.( leetcode题解，记录自己的leetcode解题之路。)
Demonstrate all the questions on LeetCode in the form of animation.（用动画的形式呈现解LeetCode题目的思路）
VGG16 models for CIFAR-10 and CIFAR-100 using Keras
Robustness vs Accuracy Survey on ImageNet
CLEVER (Cross-Lipschitz Extreme Value for nEtwork Robustness) is a robustness metric for deep neural networks