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Task oriented AI agent framework for digital workers and vertical AI agents
A curated list of awesome C++ (or C) frameworks, libraries, resources, and shiny things. Inspired by awesome-... stuff.
A list of useful payloads and bypass for Web Application Security and Pentest/CTF
aSsessMent frAmework foR deTEctors of integrity attacks to Smart meTers
A PyTorch Implementation of Jiaxuan You's Deep Gaussian Process for Crop Yield Prediction
Code of Paper D2AE: A Data Distillation Enhanced Autoencoder for Detecting Anomalous Gas Consumption
Anomaly detection Example LSTM example with Quantile Regression Keras
Multivariate time-series forecasting with LSTNET and soft-DTW loss
This repository contains the source code for fusing Sentinel-1 and Sentinel-2 time series using Multi-Output Gaussian Process Regression
ML Time Series Analysis | SARIMA, ARMA, LSTM | Power Forecasting for Sceaux, France
"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 optim…
Valid and adaptive prediction intervals for probabilistic time series forecasting
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
An Intuitive Tutorial to Gaussian Processes Regression
probabilistic forecasting with Temporal Fusion Transformer
We propose a VAE-LSTM model as an unsupervised learning approach 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
WWW 2018: Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications
MemAE for anomaly detection. -- Gong, Dong, et al. "Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection". ICCV 2019.
Weakly Supervised Video Anomaly Detection Based on Dual Dynamic Memory Network
Memory Augmented Adversarial Dual Auto Encoder for Robust Anomaly Detection
Memory Augmented Conditional Autoencoder for Anomaly Detection - Bachelor's Thesis
Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection
Official code for 'Unsupervised Anomaly Detection in Medical Images with a Memory-augmented Multi-level Cross-attentional Masked Autoencoder'
Official code for "Memory-Augmented U-Transformer for Multivariate Time Series Anomaly Detection" Code will come soon!