Flame0409's repositories
Android_ClassLoader
联手项目：
LeetCode
LeetCode training && Share
DNN_Classcify
手撕代码，以tensorflow为基础框架，实现主要包括2分类及多分类ANN，CNN，InceptionNet，RES-net，VGG-Net等
Jane-Street-Market-Prediction
Your challenge will be to use the historical data, mathematical tools, and technological tools at your disposal to create a model that gets as close to certainty as possible. You will be presented with a number of potential trading opportunities, which your model must choose whether to accept or reject. In general, if one is able to generate a highly predictive model which selects the right trades to execute, they would also be playing an important role in sending the market signals that push prices closer to “fair” values. That is, a better model will mean the market will be more efficient going forward. However, developing good models will be challenging for many reasons, including a very low signal-to-noise ratio, potential redundancy, strong feature correlation, and difficulty of coming up with a proper mathematical formulation.
GNNPapers
Must-read papers on graph neural networks (GNN)
Android_Malware_Detection-Adversarial-attack
实现了通过Android软件的Opcode的N-gram序列作为特征，在提取N-gram序列频率后，转化为7*7*7矩阵放入VGG-Net进行分类，并使用DeepFool进行对抗样本生成以及强化训练
Android-Malware-Detection
使用安卓Opcode字节码的N-gram序列特征进行恶意软件检测的完全步骤，使用算法RF，KNN
awesome_deep_learning_interpretability
深度学习近年来关于神经网络模型解释性的相关高引用/顶会论文(附带代码)
neural-networks-and-deep-learning
Code samples for my book "Neural Networks and Deep Learning"
android-malware
Collection of android malware samples
awesome-vmp
虚拟化保护（VMP壳）分析相关资料
Deep-Android-Malware-Detection
Code for Deep Android Malware Detection paper