Research

The DIG team works on knowledge graphs, language models, foundational models, learning over tabular data, graph mining, and stream mining.

The AMIE Rule Miner

AMIE is a system that can mine patterns in knowledge graphs. This project is conducted together with Luis Galarraga at INRIA Rennes.

CapyMOA

CapyMOA is a machine learning library tailored for data streams. Featuring a Python API tightly integrated with MOA (Stream Learners), PyTorch (Neural Networks), and scikit-learn (Machine Learning), CapyMOA provides a fast Python interface to leverage the state-of-the-art algorithms in the field of data streams.

River

River a Python library for online Machine Learning.

Scikit-Network

scikit-network is a Python package for the analysis of large graphs (clustering, embedding, classification, ranking).

Simplicity Theory

Simplicity theory seeks to explain the relevance of situations or events to human minds.

The YAGO Knowledge Base

YAGO is a large knowledge base constructed from Wikidata. It has legible entity names and relation names, a clean taxonomy, and enforced logical constraints.

Institutional funding

Industry collaborations