Deep learning-based outlier/anomaly detection

[VLDB'22] Anomaly Detection using Transformers, self-conditioning and adversarial training.

a time series anomaly detection method based on the calibrated one-class classifier

An easy-to-use federated learning platform

SimAD, deep learning, anomaly detection, outlier detection, time series, TNNLS, 2025. "SimAD: A Simple Dissimilarity-based Approach for Time Series Anomaly Detection", time series anomaly detection

A framework for easy running and evaluating your TSAD algorithm.

A machine learning package for streaming data in Python. The other ancestor of River.

My Java codes for the MOA framework. It includes the implementations of FHDDM, FHDDMS, and MDDMs.

[TMC 2024 Top 15 Popular Article] FedCache: A Knowledge Cache-driven Federated Learning Architecture for Personalized Edge Intelligence

Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)

Edge server, user dataset for Edge Computing research

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

Master Federated Learning in 2 Hours—Run It on Your PC!