Pinned Repositories
Pattern-recognition-homework
Using SVM and 3D-CAE for hyperspectral image classification
ad_examples
A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.
Algorithm_Interview_Notes-Chinese
2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记
AMMCNet_AAAI2021
Appearance-Motion Memory Consistency Network for Video Anomaly Detection
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
Hyperspectral-Classification
Hyperspectral-Classification Pytorch
MFTNet
MFTNet
PlotNeuralNet
Latex code for making neural networks diagrams
PyTorchDocs
PyTorch 官方中文教程包含 60 分钟快速入门教程，强化教程，计算机视觉，自然语言处理，生成对抗网络，强化学习。欢迎 Star，Fork！
Statistical-Learning-Methods
Implement Statistical Leanring Methods, Li Hang the hard way. 李航《统计学习方法》一书的硬核 Python 实现
xautzhaozhe's Repositories
xautzhaozhe/MFTNet
MFTNet
xautzhaozhe/AMMCNet_AAAI2021
Appearance-Motion Memory Consistency Network for Video Anomaly Detection
xautzhaozhe/Statistical-Learning-Methods
Implement Statistical Leanring Methods, Li Hang the hard way. 李航《统计学习方法》一书的硬核 Python 实现
xautzhaozhe/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
xautzhaozhe/PlotNeuralNet
Latex code for making neural networks diagrams
xautzhaozhe/Pattern-recognition-homework
Using SVM and 3D-CAE for hyperspectral image classification
xautzhaozhe/Hyperspectral-Classification
Hyperspectral-Classification Pytorch
xautzhaozhe/PyTorchDocs
PyTorch 官方中文教程包含 60 分钟快速入门教程，强化教程，计算机视觉，自然语言处理，生成对抗网络，强化学习。欢迎 Star，Fork！
xautzhaozhe/Algorithm_Interview_Notes-Chinese
2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记
xautzhaozhe/ad_examples
A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.