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ECQ$^{\text{x}}$: Explainability-Driven Quantization for Low-Bit and
  Sparse DNNs

ECQx^{\text{x}}x: Explainability-Driven Quantization for Low-Bit and Sparse DNNs

9 September 2021
Daniel Becking
Maximilian Dreyer
Wojciech Samek
Karsten Müller
Sebastian Lapuschkin
    MQ
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Papers citing "ECQ$^{\text{x}}$: Explainability-Driven Quantization for Low-Bit and Sparse DNNs"

2 / 2 papers shown
Title
Sparsity in Deep Learning: Pruning and growth for efficient inference
  and training in neural networks
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks
Torsten Hoefler
Dan Alistarh
Tal Ben-Nun
Nikoli Dryden
Alexandra Peste
MQ
128
679
0
31 Jan 2021
Methods for Interpreting and Understanding Deep Neural Networks
Methods for Interpreting and Understanding Deep Neural Networks
G. Montavon
Wojciech Samek
K. Müller
FaML
225
2,069
0
24 Jun 2017
1