Stars
A Model Context Protocol (MCP) server that provides translation capabilities using the DeepL API.
Identification of ontological categories for OWL ontologies.
A simple implementation of the OWL2 RL Profile on top of RDFLib: it expands the graph with all possible triples that OWL RL defines. It can be used together with RDFLib to expand an RDFLib Graph ob…
Graph Data Science: an abstraction layer in Python for building knowledge graphs, integrated with popular graph libraries – atop Pandas, NetworkX, RAPIDS, RDFlib, pySHACL, PyVis, morph-kgc, pslpyth…
[WWW 2025] A Dockerized Schema-Guided LLM Agent-based Knowledge Extraction System.
Multi-agent system for research, powered by ag2
Modular Multi-Agent System for Scientific Research Assistance
Official code for: Conformal prediction interval for dynamic time-series (conference, ICML 21 Long Presentation) AND Conformal prediction for time-series (journal, IEEE TPAMI)
KDD 2019: Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network
PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).
LoCoMotif is a time series motif discovery method that discovers variable-length motif sets in multivariate time series using time warping
pip install antialiased-cnns to improve stability and accuracy
Accompanying code for the paper "MultiADS: Defect-aware Supervision for Multi-type Anomaly Detection and Segmentation in Zero-Shot Learning"
Official code for the paper "PNI : Industrial Anomaly Detection using Position and Neighborhood Information"
Paper list and datasets for industrial image anomaly/defect detection (updating). 工业异常/瑕疵检测论文及数据集检索库(持续更新)。
Implementation of our paper "Optimizing PatchCore for Few/many-shot Anomaly Detection"
An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.
Toolbox for histopathology image analysis
Code for the paper "H-SPLID: HSIC-based Saliency Preserving Latent Information Decomposition" (NeurIPS 2025)
Minimalistic implementation for LLM-based chat assistants with Tool Use (function calling) and MCP
🚀 The fast, Pythonic way to build MCP servers and clients
Multimodal Integration with Modality-agnostic Autoencoders - Developed by LMIB @ KU Leuven