Abstract: National Airspace Systems (NAS) are cyber-physical systems that require swift air traffic management (ATM) to ensure flight safety and efficiency. With the surging demand for air travel and ...

Abstract: Despite the advancements of autonomous systems from decades of engineering, there is always the need to make them even more efficient and reliable. Machine learning holds great potential to ...

Join a talk at noon on Nov. 11 with Daniel Muthukrishna, astrophysicist and machine learning research scientist at MIT and AstroAI Fellow at Harvard on "Causal Foundation Models: Disentangling Physics ...

Communities rely on critical infrastructures that connect and power our urban systems. Due to the dramatic changes in the world climate scenarios, these systems are subject to harsh loads and severe ...

Attendance restricted to Princeton University faculty, staff and students. Algorithms make predictions about people constantly. The spread of such prediction systems has raised concerns that machine ...

LocationZoom: https://ucsd.zoom.us/j/93478513663 or NH 101 - remote ...

“Artificial Intelligence” as we know it today is, at best, a misnomer. AI is in no way intelligent, but it is artificial. It remains one of the hottest topics in industry and is enjoying a renewed ...

Discover SAP RPT-1, the relational foundation model that aims to make machine learning redundant with direct predictions on ...

After talking to machine learning and infrastructure engineers at major Internet companies across the US, Europe, and China, two groups of companies emerged. One group has invested hundreds of ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

Machine-learning models identify relationships in a data set (called the training data set) and use this training to perform operations on data that the model has not encountered before. This could ...