Other News & Events

Enter words that may appear in the title

Interpretable Machine Learning for Astrophysics, using Symbolic Regression and Graph Neural Networks

Miles Cranmer (Princeton University)
Event date
online (only)
Event type

In this talk I will argue two points. 1) Symbolic regression, a machine learning technique that fits data by iteratively searching the space of all possible analytic equations, should be a standard machine learning algorithm in astrophysics. 2) Symbolic regression can be extended to high-dimensional spaces, such as to models for N-body simulations, using the method we have developed.

APS Outstanding Referee

C. Herdeiro was nominated a 2021 Outstanding Referee by the American Physical Society (APS). The Outstanding Referee program was instituted in 2008 to recognize scientists who have been exceptionally helpful in assessing manuscripts for publication in the APS journals. This highly selective program annually recognizes about 150 of the roughly 71,000 currently active referees.

Worldwide study on influential scientists

A list of the impact of scientists' careers was revealed in late 2020 in a study coordinated by John Ioannidis, from Stanford University (USA).  It includes 34 scientists from the University of Aveiro (UA), including 2 from Gr@v.  Read the UA coverage here.