autoupdate paper list

Demonstration of LSDB and TAPE, prepared for the Rare Gems in Big Data 2024 meeting

MOMENT: A Family of Open Time-series Foundation Models

Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.

TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.

Implementation of Anomaly Detection for Time Series Using VAE-LSTM Hybrid Model in PyTorch

AI-driven identification of biomarkers from hemodialysis data.

Official repository for “PATE: Proximity-Aware Time series anomaly Evaluation”.

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

Android Application for Real-Time ECG Anomaly Detection Written in Kotlin

Package for Time Series Forecasting and Anomaly Detection Problems.

Statistical Process Monitoring in Julia

This project presents a system, namely, the abnormal-weather monitoring and curation service (AWMC), which provides people with a better understanding of abnormal weather conditions. The service can analyze a set of multivariate weather datasets (i.e., 7 meteorological datasets from 18 cities in Korea) .

A large collection of system log datasets for AI-driven log analytics [ISSRE'23]

Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™

The collection of pre-trained, state-of-the-art AI models for ailia SDK

STUMPY is a powerful and scalable Python library for modern time series analysis

Machine Learning Algorithms in Fortran

[IEEEHTC2023] Repo to analyse and predict cutting tool wear using acoustic signals.

Learning Fraud Detection from research papers and industry applications.