Contact: mpuerrer[AT]uri.eduLocation: Providence, RI, USA
We are pleased to announce a workshop on Scientific Machine Learning for Gravitational Wave Astronomy which will be held at the Institute for Computational and Experimental Research in Mathematics (ICERM) in Providence, RI, June 2-6, 2025. Applications are open at the link below.
The workshop will bring together participants from computational mathematics and gravitational wave astronomy to tackle computational challenges in leveraging data-driven methods in key areas of gravitational wave data analysis in order to maximize the science output of the ongoing and upcoming observations.
The participants will develop and apply new mathematical and computational techniques including: (i) neural network classifiers for distinguishing signals from instrumental noise, (ii) generative machine learning models for simulating realizations of non-Gaussian and non-stationary stochastic processes, (iii) surrogate models including uncertainty quantification, (iv) stochastic sampling, neural posterior estimation leveraging deep neural networks with normalizing flows or diffusion models, and (v) hierarchical Bayesian inference with non-parametric models such as Gaussian processes and simulation-based / approximate Bayesian approaches.
While the application window will be open until all slots are filled, we recommend applying by December 15.
With warm regards,
Sarah Caudill, Katerina Chatziioannou, Maya Fishbach, Brendan Keith, Jess McIver, Michael Puerrer, Joshua Speagle, and Vijay Varma