Meetings and Events

Anomaly detection is a challenging problem which can greatly benefit from the use of machine learning (ML) methods: unsupervised as well as semi-supervised. ML algorithms must be able to process complex, massive data sets and search for anomalies under extreme conditions (very low signal-to-noise ratio, real-time data, etc). The range of applications for anomaly detection methods is vast, and advances made in one scientific field can frequently be transferred to other disciplines, to the benefit of both parties involved.

More details can be found here.

The 4th edition of Cosmo21 will be hosted in Chania, Greece and will gather leading experts from around the world in statistical methods and cosmology to discuss the state-of-the-art in data analysis and interpreptation. Highlights will include topics such as Bayesian techniques, machine learning, likelihood-free inference, radio data, strong and weak gravitational lensing, joint probes, and gravitational waves. The organisers also hope to attract participants to discuss other novel developments in the field.

More details can be found here.

The 19th summer school will be held virtually via Zoom from June 3-7, 2024. The School provides an intensive program in statistical inference covering topics such as principles of probability and inference, regression and model selection, bootstrap resampling, supervised / unsupervised learning, Bayesian data analysis, Markov chain Monte Carlo (MCMC), nested sampling, time series analysis, spatial statistics, deep learning neural networks, Gaussian process, and random forest.  

Lectures will be prepared by experienced instructors in astrostatistics and will be scheduled for watching from 10:00am-4:00pm EDT (UTC-4 hours) with live Q&A session(s) each day. Lab tutorials in the form of computational notebooks will be provided as homework to reinforce the learning experience, encouraging  participants to exercise the methods with astronomical datasets illustrating realistic challenges faced in contemporary research. 

 The 2nd edition of the International Conference on Machine Learning for Astrophysics aims to unite leading researchers actively engaged in applying machine learning to astrophysical studies. This international conference is dedicated to exploring the challenges and opportunities presented by the impending Big Data era in astronomy.