The increasing complexity of modern chemical engineering processes presents significant challenges for timely and accurate anomaly detection. Traditional ...

As a University assistant, you will contribute to the work group Machine Learning with Graphs led by Prof. Nils M. Kriege. Our research focuses on the development of new methods and learning ...

Probably the most important reason for building knowledge graphs has been to answer this age-old question: “What is going to happen next?” Given the data, relationships, and timelines we know about a ...

Accurate stock trend forecasting is a central challenge in financial economics due to the highly nonlinear and interdependent nature of market dynamics. Traditional statistical and machine learning ...

The Next Frontier of Machine Learning: 2026 Breakthroughs and the Rise of World Models The landscape of artificial intelligence and ...

The number of scientific papers is growing so rapidly that scientists are no longer able to keep track of all of them, even ...

TigerGraph, the fast graph analytics platform for the enterprise, introduced TigerGraph Cloud, the simplest, most robust and cost effective way to run scalable graph analytics in the cloud. Users can ...