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Cited article:

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A large-scale heterogeneous computing framework for non-uniform sampling two-dimensional convolution applications

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Map Reconstruction of Radio Observations with Conditional Invertible Neural Networks

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Research in Astronomy and Astrophysics 23 (7) 075011 (2023)
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HEGrid: A high efficient multi-channel radio astronomical data gridding framework in heterogeneous computing environments

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Future Generation Computer Systems 138 243 (2023)
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The SOFIA FEEDBACK Legacy Survey Dynamics and Mass Ejection in the Bipolar H ii Region RCW 36

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The Astrophysical Journal 935 (2) 171 (2022)
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Five-Layer Intelligence of the Machine Brain

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A method for efficient radio astronomical data gridding on multi-core vector processor

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HCGrid: a convolution-based gridding framework for radio astronomy in hybrid computing environments

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A Space-Variant Visual Pathway Model for Data Efficient Deep Learning

Piotr Ozimek, Nina Hristozova, Lorinc Balog and Jan Paul Siebert
Frontiers in Cellular Neuroscience 13 (2019)
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Algorithms and Architectures for Parallel Processing

Qi Luo, Jian Xiao, Ce Yu, et al.
Lecture Notes in Computer Science, Algorithms and Architectures for Parallel Processing 11334 621 (2018)
https://doi.org/10.1007/978-3-030-05051-1_43