4th Summer School
Artificial Intelligence
for Astronomy
Astronomy and astrophysics are undergoing a rapid evolution towards data-driven science. Large-scale astronomical surveys and computer simulations are creating enormous amounts of datasets that require the development of new techniques for their analysis. Both complexity and sheer size of these datasets, and often the necessity of combining heterogenous sources of data, put machine learning methods as a central tool, present and future, for scientific discovery in astronomy.
The program of the 4th Institute of Space Science Summer School focused on artificial intelligence (AI) methods for astronomy research, with special focus on neural networks for image classification, natural language processing and graph neural networks. The topics covered the mathematical concepts as well as the development of software tools and applications.
Program
Lectures
- Machine Learning Overview
- Introduction to Deep Learning
- Convolutional Neural Networks
- Fully connected Neural Networks
- Advance Deep Learning
- Unsupervised Representation
- Natural Language Processing
- Graph Neural Networks
- Generative models
- Applications in astronomy
- Applications outside astronomy
Hands-on sessions
- Introduction to ML
- Neural network and backpropagation from scratch with Numpy
- Image classification
The Institute of Space Sciences welcomed around 40 Master and PhD students to the Summer School, in which they broadened their knowledge on this exciting field as well as got into contact with research groups working at the Institute in this and other fields. Registration deadlines for 2021 are listed below for reference.
◉ Registration opened from 20/05/2021 until 20/06/2021
◉ Selected participants were notified by 30/06/2021
◉ School ran from 12/07/2021 to 16/07/2021
