Self-Supervised Learning

Learning the Stellar Structure Equations via Self-supervised Physics-Informed Neural Networks
A self-supervised Physics-Informed Neural Network (PINN) framework for solving stellar structure equations as a mesh-free alternative to traditional solvers like MESA.
Manuel Ballester, Santiago Lopez-Tapia, Seth Gossage, Patrick Koller, Philipp M Srivastava, Ugur Demir, Yongseok Jo, Almudena P Marquez, Christoph Wuersch, Souvik Chakraborty, Vicky Kalogera, Aggelos Katsaggelos
Cite arXiv
Learning the Stellar Structure Equations via Self-supervised Physics-Informed Neural Networks
Size-Informed Representations for Unsupervised Image Clustering
This paper investigates how image size and preprocessing impact unsupervised clustering, introducing a late-fusion size injection strategy that significantly improves performance on heterogeneous real-world datasets.
Philipp Rajah Moura Srivastava, Charilaos Apostolidis, Saumya Pailwan, Patrick Koller, Leandros Stefanopoulos
Cite DOI IEEE Xplore
Size-Informed Representations for Unsupervised Image Clustering