121 citations · 123 across the 3 of their papers we have counts for
3 papers
cs.LG2019
Detecting Deep Neural Network Defects with Data Flow Analysis
Jiazhen Gu, Huanlin Xu, Yangfan Zhou +3
Deep neural networks (DNNs) are shown to be promising solutions in many challenging artificial intelligence tasks. However, it is very hard to figure out whether the low precision…
cs.LG2019★ 121 cited
Parameter Efficient Training of Deep Convolutional Neural Networks by Dynamic Sparse Reparameterization
Hesham Mostafa, Xin Wang
Modern deep neural networks are typically highly overparameterized. Pruning techniques are able to remove a significant fraction of network parameters with little loss in accuracy.…
cs.CV2018★ 2 cited
Explanatory Graphs for CNNs
Quanshi Zhang, Xin Wang, Ruiming Cao +3
This paper introduces a graphical model, namely an explanatory graph, which reveals the knowledge hierarchy hidden inside conv-layers of a pre-trained CNN. Each filter in a conv-la…