Serious AI forensic investigation workstation for tabular datasets: detects target leakage, structural corruption, and statistical anomalies with reproducible evidence and local AI.
Semi-supervised anomaly detection method
[ICLR 2026] The implementation of the paper Foundation Visual Encoders Are Secretly Few-Shot Anomaly Detectors
Industrial Distribution & Operations Intelligence Platform
End-to-end personal finance analytics platform with spending analysis, budget tracking, anomaly detection, spending prediction, SQLite, and Streamlit.
An open-source, ultra-fast transaction reconciliation & anomaly detection engine for Banking, Mobile Money, and Telco APIs.
Sovereign, climate-aware anomaly detection for critical infrastructure. One file. Zero dependencies. Zero data leaves your machine.
An end-to-end AI-driven sales forecasting and demand intelligence dashboard built with Python, Streamlit, and Prophet.
DecompositionUMAP: A multi-scale framework for pattern analysis and anomoly detection
Artificial Immune Systems Package (AISP) is an open-source Python library that features bio-inspired algorithms based on artificial immune systems for machine learning, pattern recognition, anomaly detection, and optimization tasks.
UPIQAL is a 100% automated Full-Reference Image Quality Assessment (FR-IQA) framework. It synthesizes deep feature statistics, probabilistic uncertainty, and spatial heuristics to replace human MOS and output spatially localized diagnostic heatmaps for visual artifacts.
Benchmarking anomaly detection on air-quality time series using a tiny autoencoder and classical methods. Includes reproducible pipeline, strict time-aware evaluation, and analysis of thresholding strategies and model performance gaps.
Kernel-Level Energy Profiling & Anomaly Detection for Android
A real-time B2B fraud detection engine using Isolation Forest, FastAPI, and Docker. Features a synthetic data generator and a human-in-the-loop analyst dashboard for risk scoring.
Advanced anomaly detection system using graph neural networks and time series analysis to identify fraudulent transactions, money laundering patterns, and market manipulation in real-time financial data streams.
Advanced anomaly detection using topological data analysis and manifold learning.
SCR# 3056.0: WGAN-based Digital Twins for Anomaly Detection
anomaly detection in mobility data
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