455 citations · 763 across the 16 of their papers we have counts for
Showing 2020Show all
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astro-ph.IM2020★ 79 cited
Self-Supervised Representation Learning for Astronomical Images
Md Abul Hayat, George Stein, Peter Harrington +2
Sky surveys are the largest data generators in astronomy, making automated tools for extracting meaningful scientific information an absolute necessity. We show that, without the n…
cs.DC2020★ 9 cited
The Case for Strong Scaling in Deep Learning: Training Large 3D CNNs with Hybrid Parallelism
Yosuke Oyama, Naoya Maruyama, Nikoli Dryden +6
We present scalable hybrid-parallel algorithms for training large-scale 3D convolutional neural networks. Deep learning-based emerging scientific workflows often require model trai…