gyyixr Goto Github PK

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gyyixr's Projects

track_sequence_anomaly_detection

由时间空间成对组成的轨迹序列，通过循环神经网络lstm，自编码器auto-encode，时空密度聚类st-dbscan做异常检测

train-ticket

Train Ticket - A Benchmark Microservice System

cnn+rnn+attention: vgg(vgg16,vgg19)+rnn(LSTM, GRU)+attention, resnet(resnet_v2_50,resnet_v2_101,resnet_v2_152)+rnnrnn(LSTM, GRU)+attention, inception_v4+rnn(LSTM, GRU)+attention, inception_resnet_v2+rnn(LSTM, GRU)+attention,..... vgg(vgg16,vgg19), resnet(resnet_v2_50,resnet_v2_101,resnet_v2_152), inception_v4, inception_resnet_v2,.....

ts_forecast

Time Series Forecast with Influxdb and Loudml

tsbs

Time Series Benchmark Suite, a tool for comparing and evaluating databases for time series data

unsupervised-deep-learning-framework-for-anomaly-detection-in-time-series-

Unsupervised deep learning framework with online(MLP: prediction-based, 1 D Conv and VAE: reconstruction-based, Wavenet: prediction-based) settings for anaomaly detection in time series data

vade

Python code for paper - Variational Deep Embedding : A Generative Approach to Clustering

vade-pytorch

the reproduce of Variational Deep Embedding : A Generative Approach to Clustering Requirements by pytorch

vae-for-anomaly-detection

MLP_VAE, Anomaly Detection, LSTM_VAE, Multivariate Time-Series Anomaly Detection, IndRNN_VAE, Tensorflow

vae-lstm-for-anomaly-detection

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

var-attn

Latent Alignment and Variational Attention

variational-lstm-autoencoder

Lstm variational auto-encoder API for time series anomaly detection and features extraction

xgbod

Supplementary material for IJCNN paper "XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning"

zap

Blazing fast, structured, leveled logging in Go.

gyyixr Goto Github PK

gyyixr's Projects

track_sequence_anomaly_detection

train-ticket

train_arch

ts_forecast

tsbs

unsupervised-deep-learning-framework-for-anomaly-detection-in-time-series-

vade

vade-pytorch

vae-for-anomaly-detection

vae-lstm-for-anomaly-detection

var-attn

variational-lstm-autoencoder

xgbod

zap

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