15 citations · 16 across the 3 of their papers we have counts for
3 papers
Tuning neural posterior estimation for gravitational wave inference
Alex Kolmus, Justin Janquart, Tomasz Baka +3
Modern simulation-based inference techniques use neural networks to solve inverse problems efficiently. One notable strategy is neural posterior estimation (NPE), wherein a neural…
Swift sky localization of gravitational waves using deep learning seeded importance sampling
Alex Kolmus, Grégory Baltus, Justin Janquart +3
Fast, highly accurate, and reliable inference of the sky origin of gravitational waves would enable real-time multi-messenger astronomy. Current Bayesian inference methodologies, a…
Gaussian Processes with Skewed Laplace Spectral Mixture Kernels for Long-term Forecasting
Kai Chen, Twan van Laarhoven, Elena Marchiori
Long-term forecasting involves predicting a horizon that is far ahead of the last observation. It is a problem of high practical relevance, for instance for companies in order to d…