Hi there!
I am a physicist and a software engineer with a passion for applying Machine Learning, Bayesian modeling, and High-Performance Computing to natural sciences. This webpage contains various content that I considered interesting enough to share with the world. You can find here my publications and blog posts.
Featured Content
IrisML - Neural Posterior Estimation for Spectral Energy Distribution fitting
(2025)
- Authors: Mateusz Kapusta
- Journal: ICML 2025: Machine Learning for Astrophysics workshop Link
Fast and reliable real-time inference for astronomical data? Now possible with Simulation-Based Inference.
GMVAE clustering applied to RNA sequencing
(2023)
Traditional clustering methods typically rely on the raw, observed features of data. However, we can often achieve better results by using Variational Autoencoders (VAEs) to create an embedded representation of the data first.