211 citations · 479 across the 30 of their papers we have counts for
7 papers · 1 filter
Neural Network Based Point Spread Function Deconvolution For Astronomical Applications
Hong Wang, Sreevarsha Sreejith, Yuewei Lin +3
Optical astronomical images are strongly affected by the point spread function (PSF) of the optical system and the atmosphere (seeing) which blurs the observed image. The amount of…
Uncertainty-aware predictions of molecular X-ray absorption spectra using neural network ensembles
Animesh Ghose, Mikhail Segal, Fanchen Meng +7
As machine learning (ML) methods continue to be applied to a broad scope of problems in the physical sciences, uncertainty quantification is becoming correspondingly more important…
DUNE Software and High Performance Computing
Bonnie Fleming, Kyle Knoepfel, Meifeng Lin +6
DUNE, like other HEP experiments, faces a challenge related to matching execution patterns of our production simulation and data processing software to the limitations imposed by m…
UVCGAN: UNet Vision Transformer cycle-consistent GAN for unpaired image-to-image translation
Dmitrii Torbunov, Yi Huang, Haiwang Yu +5
Unpaired image-to-image translation has broad applications in art, design, and scientific simulations. One early breakthrough was CycleGAN that emphasizes one-to-one mappings betwe…
A Deep Finite Difference Emulator for the Fast Simulation of Coupled Viscous Burgers' Equation
Xihaier Luo, Yihui Ren, Wei Xu +3
This work proposes a deep learning-based emulator for the efficient computation of the coupled viscous Burgers' equation with random initial conditions. In a departure from traditi…
A Bayesian Deep Learning Approach to Near-Term Climate Prediction
Xihaier Luo, Balasubramanya T. Nadiga, Yihui Ren +3
Since model bias and associated initialization shock are serious shortcomings that reduce prediction skills in state-of-the-art decadal climate prediction efforts, we pursue a comp…