Search Results for author:
Found 3 papers, 0 papers with code
Sparse $L^1$-Autoencoders for Scientific Data Compression
Scientific datasets present unique challenges for machine learning-driven compression methods, including more stringent requirements on accuracy and mitigation of potential invalidating artifacts.
Integrating Deep Learning in Domain Sciences at Exascale
This paper discusses the necessities of an HPC deep learning framework and how those needs can be provided (e. g., as in MagmaDNN) through a deep integration with existing HPC libraries, such as MAGMA and its modular memory management, MPI, CuBLAS, CuDNN, MKL, and HIP.
Feature Selection and Classification of Hyperspectral Images With Support Vector Machines
Hyperspectral images consist of large number of bands which require sophisticated analysis to extract.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
