267 citations · 284 across the 7 of their papers we have counts for
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cs.CV2021★ 1 cited
Automatic Neural Network Pruning that Efficiently Preserves the Model Accuracy
Thibault Castells, Seul-Ki Yeom
Neural networks performance has been significantly improved in the last few years, at the cost of an increasing number of floating point operations per second (FLOPs). However, mor…
cs.CV2021★ 8 cited
Toward Compact Deep Neural Networks via Energy-Aware Pruning
Seul-Ki Yeom, Kyung-Hwan Shim, Jee-Hyun Hwang
Despite the remarkable performance, modern deep neural networks are inevitably accompanied by a significant amount of computational cost for learning and deployment, which may be i…