Barry de Bruin

Generating author description...

All published works

Action	Title	Year	Authors
+	CONVOLVE: Smart and seamless design of smart edge processors	2022	Manil Dev Gomony Floran A. M. de Putter A. Gebregiorgis G. Paulin L. Mei Vikram Jain S. Hamdioui V. Sanchez Tobias Grosser Marc Geilen
+ PDF Chat	Quantization of deep neural networks for accumulator-constrained processors	2019	Barry de Bruin Zoran Živković Henk Corporaal

Common Coauthors

Coauthor	Papers Together
G. Paulin	1
M. Ghogho	1
F. Gurkaynak	1
S. Ainsworth	1
S. Davidson	1
T. Güneysu	1
A. Gebregiorgis	1
Sander Stuijk	1
L. Mei	1
O. Karrakchou	1
Dimitrios Soudris	1
M. Verhelst	1
S. Hamdioui	1
S. Eissa	1
Tobias Grosser	1
Floran A. M. de Putter	1
Marc Geilen	1
Zoran Živković	1
V. Sanchez	1
Federico Corradi	1
L. Benini	1
H. Corporaal	1
S. De	1
Vikram Jain	1
A. Jimborean	1
Henk Corporaal	1
F. Zenke	1
R. Bishnoi	1
Manil Dev Gomony	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Estimating or Propagating Gradients Through Stochastic Neurons	2013	Yoshua Bengio	1
+	One weird trick for parallelizing convolutional neural networks	2014	Alex Krizhevsky	1
+	Training deep neural networks with low precision multiplications	2014	Matthieu Courbariaux Yoshua Bengio Jean‐Pierre David	1
+	Deep Learning with Limited Numerical Precision	2015	Suyog Gupta Ankur Agrawal Kailash Gopalakrishnan Pritish Narayanan	1
+	Striving for Simplicity: The All Convolutional Net	2014	Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller	1
+ PDF Chat	XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks	2016	Mohammad Rastegari Vicente Ordóñez Joseph Redmon Ali Farhadi	1
+	Hardware-oriented Approximation of Convolutional Neural Networks	2016	Philipp Gysel Mohammad Motamedi Soheil Ghiasi	1
+	DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients	2016	Shuchang Zhou Yuxin Wu Zekun Ni Xinyu Zhou He Wen Yuheng Zou	1
+	Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations	2016	Itay Hubara Matthieu Courbariaux Daniel Soudry Ran El‐Yaniv Yoshua Bengio	1
+	Deep Convolutional Neural Network Inference with Floating-point Weights and Fixed-point Activations	2017	Liangzhen Lai Naveen Suda Vikas Chandra	1
+	Flexpoint: An Adaptive Numerical Format for Efficient Training of Deep Neural Networks	2017	Urs Köster Tristan J. Webb Xin Wang Marcel Nassar Arjun K. Bansal William Constable Oğuz H. Elibol Scott Gray Stewart Hall Luke Hornof	1
+	Mixed Precision Training of Convolutional Neural Networks using Integer Operations	2018	Dipankar Das Naveen Mellempudi Dheevatsa Mudigere Dhiraj D. Kalamkar Sasikanth Avancha Kunal Banerjee Srinivas Sridharan K. Vaidyanathan Bharat Kaul Evangelos Georganas	1
+	Flexpoint: An Adaptive Numerical Format for Efficient Training of Deep Neural Networks	2017	Urs Köster Tristan J. Webb Xin Wang Marcel Nassar Arjun K. Bansal William Constable Oğuz H. Elibol Scott Gray Stewart Hall Luke Hornof	1
+	Accumulation bit-width scaling for ultra-low precision training of deep networks	2019	Charbel Sakr Naigang Wang Chia Yu Chen Jungwook Choi Ankur Agrawal Naresh R. Shanbhag Kailash Gopalakrishnan	1
+	Striving for Simplicity: The All Convolutional Net	2014	Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller	1
+	Mixed Precision Training of Convolutional Neural Networks using Integer Operations	2018	Dipankar Das Naveen Mellempudi Dheevatsa Mudigere Dhiraj D. Kalamkar Sasikanth Avancha Kunal Banerjee Srinivas Sridharan K. Vaidyanathan Bharat Kaul Evangelos Georganas	1
+	Training deep neural networks with low precision multiplications	2014	Matthieu Courbariaux Yoshua Bengio Jean‐Pierre David	1
+	Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks	2019	Charbel Sakr Naigang Wang Chia‐Yu Chen Jungwook Choi Ankur Agrawal Naresh R. Shanbhag Kailash Gopalakrishnan	1