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Found 4 papers, 3 papers with code
Spherical Fourier Neural Operators: Learning Stable Dynamics on the Sphere
Fourier Neural Operators (FNOs) have proven to be an efficient and effective method for resolution-independent operator learning in a broad variety of application areas across scientific machine learning.
MetaCache-GPU: Ultra-Fast Metagenomic Classification
In the context of an ever-growing number of reference genomes, MetaCache-GPU is the first metagenomic classifier that makes analysis pipelines with on-demand composition of large-scale reference genome sets practical.
WarpCore: A Library for fast Hash Tables on GPUs
The rapidly growing amount of data emerging in many fields motivated the need for accelerated hash tables designed for modern parallel architectures.
Distributed, Parallel, and Cluster Computing
$ν$-net: Deep Learning for Generalized Biventricular Cardiac Mass and Function Parameters
Conclusions: Biventricular mass and function parameters can be determined reliably in high quality by applying a deep neural network for cardiac MRI segmentation, especially in the anatomically complex right ventricle.
