XiTAOzi

XiTAOzi's Stars

• scutan90/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

  Language:JavaScript55.2k2.2k19015.9k

• huihut/interview

  📚 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, including language, program library, data structure, algorithm, system, network, link loading library, interview experience, recruitment, recommendation, etc.

  Language:C++35.2k866638k

• ldcsaa/HP-Socket

  High Performance TCP/UDP/HTTP Communication Component

  Language:C5.8k5132701.8k

• openvinotoolkit/anomalib

  An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.

  Language:Python3.9k41933703

• Newmu/dcgan_code

  Deep Convolutional Generative Adversarial Networks

  Language:Python3.5k15734694

• shanglianlm0525/PyTorch-Networks

  Pytorch implementation of cnn network

  Language:Python1.9k3620486

• soumith/dcgan.torch

  A torch implementation of http://arxiv.org/abs/1511.06434

  Language:Lua1.5k5489414

• juntang-zhuang/Adabelief-Optimizer

  Repository for NeurIPS 2020 Spotlight "AdaBelief Optimizer: Adapting stepsizes by the belief in observed gradients"

  Language:Jupyter Notebook1.1k2351109

• amazon-science/patchcore-inspection

  Language:Python80514105159

• YixinChen-AI/CVAE-GAN-zoos-PyTorch-Beginner

  For beginner, this will be the best start for VAEs, GANs, and CVAE-GAN. This contains AE, DAE, VAE, GAN, CGAN, DCGAN, WGAN, WGAN-GP, VAE-GAN, CVAE-GAN. All use PyTorch.

  Language:Python728212110

• christiancosgrove/pytorch-spectral-normalization-gan

  Paper by Miyato et al. https://openreview.net/forum?id=B1QRgziT-

  Language:Python6781718109

• lin-shuyu/VAE-LSTM-for-anomaly-detection

  We propose a VAE-LSTM model as an unsupervised learning approach for anomaly detection in time series.

  Language:Jupyter Notebook483101187

• soumith/talks

  Language:Jupyter Notebook26521051

• Fengrui-Liu/StreamAD

  Online anomaly detection for data streams/ Real-time anomaly detection for time series data.

  Language:Python1176223

• seangal/dcgan_vae_pytorch

  dcgan combined with vae in pytorch!

  Language:Python1173532

• JGuymont/vae-anomaly-detector

  Experiments on unsupervised anomaly detection using variational autoencoder. The variational autoencoder is implemented in Pytorch.

  Language:Python665319

• alandtsang/mydpdkdns

  dns server with high performance, based on dpdk.

  Language:C++516343

• jnothman/searchgrid

  Helpers for constructing scikit-learn grid search

  Language:Python37493

• bcaosudo/AE-GAN

  AE-GAN

  Language:Python21301

• HardikPrabhu/EnergyTS-GANomaly-with-Parallel-Reconstruction

  Code for our paper "Generative Adversarial Network with Soft-Dynamic Time Warping and Parallel Reconstruction for Energy Time Series Anomaly Detection" and its extension.

  Language:Python21204

• ashukid/anomaly-detection-in-ecg-signal

  Official implementation of "Regularised Encoder-Decoder Architecture for Anomaly Detection in ECG Time Signals"

  Language:Jupyter Notebook19220

• hs366399/Image-Super-Resolution-Using-VAE-GAN-with-PyTorch

  The model uses the AE-GAN (Autoencoder Generative Adversarial Network) architecture for generating upsampled images. The model is trained on Celeb-A image (1024 x 1024) dataset where input image is of 128x128 and generated image is of shape 480x480.

  Language:Python14203

• sathishprasad/Detecting-Anomaly-in-ECG-Data-Using-AutoEncoder-with-PyTorch

  This project, "Detecting Anomaly in ECG Data Using AutoEncoder with PyTorch," focuses on leveraging an LSTM-based Autoencoder for identifying irregularities in ECG signals. It employs PyTorch to train and evaluate the model on datasets of normal and anomalous heart patterns, emphasizing real-time anomaly detection to enhance cardiac monitoring.

  Language:Jupyter Notebook9101

• Ye-Xiao12/Network_programming

  c++高并发网络编程项目

  Language:C++7

• zideliu/AE-StyleGAN

  AE-StyleGAN: Improved Training of Style-Based Auto-Encoders

  Language:Python4200

• gm3g11/AE-VAE-GAN

  Try AE,VAE,DCGAM,AEWGAN, VAEDCGAN on brain dataset in Pytorch

  Language:Python3200

• Ra1demmmm/Autoencoder-based-Outlier-Detection

  The implementation of paper "Improving Autoencoder-based Outlier Detection with Adjustable Probabilistic Reconstruction Error and Mean-shift Outlier Scoring".

  Language:Python30

• NFSamuel47/GAN_AE-based_anomaly_detection

  Language:Python21

• git-dhruv/CycleGAN-Pytorch

  Pytorch Implementation of CycleGAN, GANs and VAE

  Language:Jupyter Notebook1100

• macallen7/current_based_anomaly_detection_with_GAN_and_AE

  Language:Jupyter Notebook1