196 citations · 2.8k across the 144 of their papers we have counts for
5 papers · 1 filter
Generating Images of the M87* Black Hole Using GANs
Arya Mohan, Pavlos Protopapas, Keerthi Kunnumkai +8
In this paper, we introduce a novel data augmentation methodology based on Conditional Progressive Generative Adversarial Networks (CPGAN) to generate diverse black hole (BH) image…
One-Shot Transfer Learning for Nonlinear ODEs
Wanzhou Lei, Pavlos Protopapas, Joy Parikh
We introduce a generalizable approach that combines perturbation method and one-shot transfer learning to solve nonlinear ODEs with a single polynomial term, using Physics-Informed…
Faster Bayesian inference with neural network bundles and new results for models
Augusto T. Chantada, Susana J. Landau, Pavlos Protopapas +2
In the last few years, there has been significant progress in the development of machine learning methods tailored to astrophysics and cosmology. We have recently applied one of th…
Positional Encodings for Light Curve Transformers: Playing with Positions and Attention
Daniel Moreno-Cartagena, Guillermo Cabrera-Vives, Pavlos Protopapas +3
We conducted empirical experiments to assess the transferability of a light curve transformer to datasets with different cadences and magnitude distributions using various position…
Residual-based error bound for physics-informed neural networks
Shuheng Liu, Xiyue Huang, Pavlos Protopapas
Neural networks are universal approximators and are studied for their use in solving differential equations. However, a major criticism is the lack of error bounds for obtained sol…