most citedSpeedup deep learning models on GPU by taking advantage of efficient unstructured pruning and bit-width reduction

2 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2021★ 2 cited

Speedup deep learning models on GPU by taking advantage of efficient unstructured pruning and bit-width reduction

Marcin Pietroń, Dominik Żurek

This work is focused on the pruning of some convolutional neural networks (CNNs) and improving theirs efficiency on graphic processing units (GPU) by using a direct sparse algorith…

cs.NE2021

Neuroevolution deep learning architecture search for estimation of river surface elevation from photogrammetric Digital Surface Models

Radosław Szostak, Marcin Pietroń, Mirosław Zimnoch +3

Development of the new methods of surface water observation is crucial in the perspective of increasingly frequent extreme hydrological events related to global warming and increas…