wangchz13

nwpu-cram

西北工业大学/西工大/nwpu/npu软件学院复习(突击)资料！！

gpt-computer-assistant

Intelligence development framework in python for your product like Apple Intelligence

awesome-cpp

A curated list of awesome C++ (or C) frameworks, libraries, resources, and shiny things. Inspired by awesome-... stuff.

PayloadsAllTheThings

A list of useful payloads and bypass for Web Application Security and Pentest/CTF

CTFs

RootMeProgrammingChallenges

smartest

aSsessMent frAmework foR deTEctors of integrity attacks to Smart meTers

ts2vec

A universal time series representation learning framework

MNAD

An official implementation of "Learning Memory-guided Normality for Anomaly Detection" (CVPR 2020) in PyTorch.

CRAD

The official repository of Continuous Memory Representation for Anomaly Detection

Urban_Concept_Drift

[CIKM 2023] MemDA: Forecasting Urban Time Series with Memory-based Drift Adaptation

MQRNN

Multi-Quantile Recurrent Neural Network for Quantile Regression

pycrop-yield-prediction

A PyTorch Implementation of Jiaxuan You's Deep Gaussian Process for Crop Yield Prediction

PyDeepGP

Deep Gaussian Processes in Python

Gas_Anomaly_Detection

Code of Paper D2AE: A Data Distillation Enhanced Autoencoder for Detecting Anomalous Gas Consumption

Quantile-LSTM

Anomaly_detection

Anomaly detection Example LSTM example with Quantile Regression Keras

Time-Series-Forecast-with-Deep-Hybrid-Architecture

Multivariate time-series forecasting with LSTNET and soft-DTW loss

mogptk

Multi-Output Gaussian Process Toolkit

Synergy-of-S1-and-S2-time-series

This repository contains the source code for fusing Sentinel-1 and Sentinel-2 time series using Multi-Output Gaussian Process Regression

Household-Power-Consumption-Forecasting

ML Time Series Analysis | SARIMA, ARMA, LSTM | Power Forecasting for Sceaux, France

-Predictive-Modeling-of-Household-Energy-Consumption-

"Explore predictive modeling of household energy use with 'SLR.ipynb'. It covers data prep, analysis, and regression techniques to forecast energy needs, focusing on environmental impacts and optimization methods."

Ensemble-Conformalized-Quantile-Regression

Valid and adaptive prediction intervals for probabilistic time series forecasting

ODKL

GPR-RF-Electricity-forecast

Monthly-Electricity-forecast use GPR-RFr 某区域月电量预测，采用高斯过程回归、随机森林回归预测日电量，通过日电量累加的方式来获得月电量的预测

Gaussian-Process-Regression-Tutorial

An Intuitive Tutorial to Gaussian Processes Regression

TFT_darts

probabilistic forecasting with Temporal Fusion Transformer

VAE-LSTM-for-anomaly-detection

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

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

donut

WWW 2018: Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications