Pinned Repositories
AdderNet
Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"
beego_blog
beego+layui go入门开发 简洁美观的个人博客系统
DCSO
Supplementary material for KDD 2018 workshop "DCSO: Dynamic Combination of Detector Scores for Outlier Ensembles"
deepcorr
JsCalendar
使用JS写的一个日历
LSTM-FCN
Codebase for the paper LSTM Fully Convolutional Networks for Time Series Classification
mockingbird
Keras with Tensorflow implementation of our paper "Mockingbird: Defending Against Deep-Learning-Based Website Fingerprinting Attacks with Adversarial Traces" which is published in IEEE Transactions on Information Forensics and Security (TIFS).
smote_variants
A collection of 85 minority oversampling techniques (SMOTE) for imbalanced learning with multi-class oversampling and model selection features
WebsiteFingerprinting
Codes for WF attacks, defenses
k-FP
Benchmarks for the k-FP WF attack
jachinchen's Repositories
jachinchen/JsCalendar
使用JS写的一个日历
jachinchen/AdderNet
Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"
jachinchen/beego_blog
beego+layui go入门开发 简洁美观的个人博客系统
jachinchen/DCSO
Supplementary material for KDD 2018 workshop "DCSO: Dynamic Combination of Detector Scores for Outlier Ensembles"
jachinchen/deepcorr
jachinchen/LSTM-FCN
Codebase for the paper LSTM Fully Convolutional Networks for Time Series Classification
jachinchen/mockingbird
Keras with Tensorflow implementation of our paper "Mockingbird: Defending Against Deep-Learning-Based Website Fingerprinting Attacks with Adversarial Traces" which is published in IEEE Transactions on Information Forensics and Security (TIFS).
jachinchen/smote_variants
A collection of 85 minority oversampling techniques (SMOTE) for imbalanced learning with multi-class oversampling and model selection features
jachinchen/WebsiteFingerprinting
Codes for WF attacks, defenses
jachinchen/deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
jachinchen/DeepLearning-500-questions
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06
jachinchen/DLWF
Source code for our NDSS'18 paper "Automated Website Fingerprinting through Deep Learning"
jachinchen/English_Learning
jachinchen/FFmpeg
Mirror of https://git.ffmpeg.org/ffmpeg.git
jachinchen/golang-design-pattern
设计模式 Golang实现－《研磨设计模式》读书笔记
jachinchen/handson-ml
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
jachinchen/interview-go
golang面试题集合
jachinchen/k-FP
Benchmarks for the k-FP WF attack
jachinchen/kWTA-Activation
jachinchen/Machine-Learning
:zap:机器学习实战（Python3）：kNN、决策树、贝叶斯、逻辑回归、SVM、线性回归、树回归
jachinchen/pyod
A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)
jachinchen/recipes
📁 Examples for 🚀 Fiber
jachinchen/Review201704
网络安全，Web 数据挖掘，日语2
jachinchen/SCUT-Bachelor-Thesis-Template
Latex template for the bachelor graduation thesis of South China University of Technology (SCUT) 华南理工大学 本科毕业论文LaTeX模板
jachinchen/training
Learning Golang one day