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Convolutional Networks for Fast, Energy-Efficient Neuromorphic Computing
v1v2 (latest)

Convolutional Networks for Fast, Energy-Efficient Neuromorphic Computing

28 March 2016
S. K. Esser
P. Merolla
John V. Arthur
A. Cassidy
R. Appuswamy
Alexander Andreopoulos
David J. Berg
J. McKinstry
T. Melano
D. Barch
C. D. Nolfo
Pallab Datta
A. Amir
B. Taba
M. Flickner
D. Modha
    3DH
ArXiv (abs)PDFHTML

Papers citing "Convolutional Networks for Fast, Energy-Efficient Neuromorphic Computing"

45 / 195 papers shown
Title
FFT-Based Deep Learning Deployment in Embedded Systems
FFT-Based Deep Learning Deployment in Embedded Systems
Sheng Lin
Ning Liu
M. Nazemi
Hongjia Li
Caiwen Ding
Yanzhi Wang
Massoud Pedram
57
54
0
13 Dec 2017
Towards Accurate Binary Convolutional Neural Network
Towards Accurate Binary Convolutional Neural Network
Xiaofan Lin
Cong Zhao
Wei Pan
MQ
112
650
0
30 Nov 2017
Bridging the Gap Between Neural Networks and Neuromorphic Hardware with
  A Neural Network Compiler
Bridging the Gap Between Neural Networks and Neuromorphic Hardware with A Neural Network Compiler
Yu Ji
Youhui Zhang
Wenguang Chen
Yuan Xie
102
56
0
15 Nov 2017
Efficient Computation in Adaptive Artificial Spiking Neural Networks
Efficient Computation in Adaptive Artificial Spiking Neural Networks
Davide Zambrano
Roeland Nusselder
H. Scholte
S. Bohté
61
22
0
13 Oct 2017
Neural and Synaptic Array Transceiver: A Brain-Inspired Computing
  Framework for Embedded Learning
Neural and Synaptic Array Transceiver: A Brain-Inspired Computing Framework for Embedded Learning
Georgios Detorakis
Sadique Sheik
C. Augustine
Somnath Paul
Bruno U. Pedroni
N. Dutt
J. Krichmar
Gert Cauwenberghs
Emre Neftci
87
29
0
29 Sep 2017
CirCNN: Accelerating and Compressing Deep Neural Networks Using
  Block-CirculantWeight Matrices
CirCNN: Accelerating and Compressing Deep Neural Networks Using Block-CirculantWeight Matrices
Caiwen Ding
Siyu Liao
Yanzhi Wang
Zhe Li
Ning Liu
...
Yipeng Zhang
Jian Tang
Qinru Qiu
Xinyu Lin
Bo Yuan
GNN
73
260
0
29 Aug 2017
A scalable multi-core architecture with heterogeneous memory structures
  for Dynamic Neuromorphic Asynchronous Processors (DYNAPs)
A scalable multi-core architecture with heterogeneous memory structures for Dynamic Neuromorphic Asynchronous Processors (DYNAPs)
S. Moradi
Ning Qiao
F. Stefanini
Giacomo Indiveri
80
487
0
14 Aug 2017
On The Robustness of a Neural Network
On The Robustness of a Neural Network
El-Mahdi El-Mhamdi
R. Guerraoui
Sébastien Rouault
OOD
72
19
0
25 Jul 2017
When Neurons Fail
When Neurons Fail
El-Mahdi El-Mhamdi
R. Guerraoui
57
36
0
27 Jun 2017
Hardware-efficient on-line learning through pipelined truncated-error
  backpropagation in binary-state networks
Hardware-efficient on-line learning through pipelined truncated-error backpropagation in binary-state networks
H. Elsayed
Bruno U. Pedroni
Sadique Sheik
Gert Cauwenberghs
54
8
0
15 Jun 2017
Spatio-Temporal Backpropagation for Training High-performance Spiking
  Neural Networks
Spatio-Temporal Backpropagation for Training High-performance Spiking Neural Networks
Yujie Wu
Lei Deng
Guoqi Li
Jun Zhu
Luping Shi
104
1,040
0
08 Jun 2017
GXNOR-Net: Training deep neural networks with ternary weights and
  activations without full-precision memory under a unified discretization
  framework
GXNOR-Net: Training deep neural networks with ternary weights and activations without full-precision memory under a unified discretization framework
Lei Deng
Peng Jiao
Jing Pei
Zhenzhi Wu
Guoqi Li
MQ
97
20
0
25 May 2017
First-spike based visual categorization using reward-modulated STDP
First-spike based visual categorization using reward-modulated STDP
Milad Mozafari
Saeed Reza Kheradpisheh
T. Masquelier
A. Nowzari-Dalini
M. Ganjtabesh
81
159
0
25 May 2017
The High-Dimensional Geometry of Binary Neural Networks
The High-Dimensional Geometry of Binary Neural Networks
Alexander G. Anderson
C. P. Berg
MQ
91
76
0
19 May 2017
Improving classification accuracy of feedforward neural networks for
  spiking neuromorphic chips
Improving classification accuracy of feedforward neural networks for spiking neuromorphic chips
Antonio Jimeno Yepes
Jianbin Tang
B. Mashford
59
14
0
19 May 2017
A Survey of Neuromorphic Computing and Neural Networks in Hardware
A Survey of Neuromorphic Computing and Neural Networks in Hardware
Catherine D. Schuman
T. Potok
Robert M. Patton
J. Birdwell
Mark E. Dean
Garrett S. Rose
J. Plank
143
699
0
19 May 2017
Reconfiguring the Imaging Pipeline for Computer Vision
Reconfiguring the Imaging Pipeline for Computer Vision
Mark Buckler
Suren Jayasuriya
Adrian Sampson
113
105
0
11 May 2017
Factorization tricks for LSTM networks
Factorization tricks for LSTM networks
Oleksii Kuchaiev
Boris Ginsburg
104
113
0
31 Mar 2017
Efficient Processing of Deep Neural Networks: A Tutorial and Survey
Efficient Processing of Deep Neural Networks: A Tutorial and Survey
Vivienne Sze
Yu-hsin Chen
Tien-Ju Yang
J. Emer
AAML3DV
120
3,038
0
27 Mar 2017
Pattern representation and recognition with accelerated analog
  neuromorphic systems
Pattern representation and recognition with accelerated analog neuromorphic systems
Mihai A. Petrovici
Sebastian Schmitt
Johann Klähn
Robert D. St. Louis
A. Schroeder
...
Wolfgang Maass
R. Schüffny
Christian Mayr
Johannes Schemmel
K. Meier
63
15
0
17 Mar 2017
A Study of Complex Deep Learning Networks on High Performance,
  Neuromorphic, and Quantum Computers
A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers
T. Potok
Catherine D. Schuman
Steven R. Young
Robert M. Patton
F. Spedalieri
Jeremy Liu
Ke-Thia Yao
Garrett S. Rose
Gangotree Chakma
66
82
0
15 Mar 2017
Robustness from structure: Inference with hierarchical spiking networks
  on analog neuromorphic hardware
Robustness from structure: Inference with hierarchical spiking networks on analog neuromorphic hardware
Mihai A. Petrovici
A. Schroeder
O. Breitwieser
Andreas Grübl
Johannes Schemmel
K. Meier
46
3
0
12 Mar 2017
Large-scale image analysis using docker sandboxing
Large-scale image analysis using docker sandboxing
B. Sengupta
E. Vazquez
Michele Sasdelli
Y. Qian
M. Peniak
L. Netherton
G. Delfino
13
4
0
07 Mar 2017
Neuromorphic Hardware In The Loop: Training a Deep Spiking Network on
  the BrainScaleS Wafer-Scale System
Neuromorphic Hardware In The Loop: Training a Deep Spiking Network on the BrainScaleS Wafer-Scale System
Sebastian Schmitt
Johann Klaehn
G. Bellec
Andreas Grübl
Maurice Guettler
...
Robert Legenstein
Wolfgang Maass
Christian Mayr
Johannes Schemmel
K. Meier
61
138
0
06 Mar 2017
Energy Saving Additive Neural Network
Energy Saving Additive Neural Network
Arman Afrasiyabi
Ozan Yildiz
Baris Nasir
Fatoş T. Yarman Vural
A. Enis Cetin
48
2
0
09 Feb 2017
Scaling Binarized Neural Networks on Reconfigurable Logic
Scaling Binarized Neural Networks on Reconfigurable Logic
Nicholas J. Fraser
Yaman Umuroglu
Giulio Gambardella
Michaela Blott
Philip H. W. Leong
Magnus Jahre
K. Vissers
MQ
92
57
0
12 Jan 2017
Neuromorphic Deep Learning Machines
Neuromorphic Deep Learning Machines
Emre Neftci
C. Augustine
Somnath Paul
Georgios Detorakis
BDL
220
260
0
16 Dec 2016
Delta Networks for Optimized Recurrent Network Computation
Delta Networks for Optimized Recurrent Network Computation
Daniel Neil
Junhaeng Lee
T. Delbruck
Shih-Chii Liu
106
66
0
16 Dec 2016
Theory and Tools for the Conversion of Analog to Spiking Convolutional
  Neural Networks
Theory and Tools for the Conversion of Analog to Spiking Convolutional Neural Networks
Bodo Rueckauer
Iulia-Alexandra Lungu
Yuhuang Hu
Michael Pfeiffer
70
125
0
13 Dec 2016
Enabling Bio-Plausible Multi-level STDP using CMOS Neurons with
  Dendrites and Bistable RRAMs
Enabling Bio-Plausible Multi-level STDP using CMOS Neurons with Dendrites and Bistable RRAMs
Xinyu Wu
V. Saxena
46
7
0
05 Dec 2016
FINN: A Framework for Fast, Scalable Binarized Neural Network Inference
FINN: A Framework for Fast, Scalable Binarized Neural Network Inference
Yaman Umuroglu
Nicholas J. Fraser
Giulio Gambardella
Michaela Blott
Philip H. W. Leong
Magnus Jahre
K. Vissers
MQ
110
1,005
0
01 Dec 2016
SC-DCNN: Highly-Scalable Deep Convolutional Neural Network using
  Stochastic Computing
SC-DCNN: Highly-Scalable Deep Convolutional Neural Network using Stochastic Computing
Ao Ren
Ji Li
Zhe Li
Caiwen Ding
Xuehai Qian
Qinru Qiu
Bo Yuan
Yanzhi Wang
78
198
0
18 Nov 2016
Training Spiking Deep Networks for Neuromorphic Hardware
Training Spiking Deep Networks for Neuromorphic Hardware
Eric Hunsberger
C. Eliasmith
74
133
0
16 Nov 2016
Sigma Delta Quantized Networks
Sigma Delta Quantized Networks
Peter O'Connor
Max Welling
70
49
0
07 Nov 2016
A Self-Driving Robot Using Deep Convolutional Neural Networks on
  Neuromorphic Hardware
A Self-Driving Robot Using Deep Convolutional Neural Networks on Neuromorphic Hardware
Tiffany Hwu
Jacob Isbell
Nicolas Oros
J. Krichmar
58
49
0
04 Nov 2016
Deep counter networks for asynchronous event-based processing
Deep counter networks for asynchronous event-based processing
Jonathan Binas
Giacomo Indiveri
Michael Pfeiffer
BDL
38
5
0
02 Nov 2016
Fast and Efficient Asynchronous Neural Computation with Adapting Spiking
  Neural Networks
Fast and Efficient Asynchronous Neural Computation with Adapting Spiking Neural Networks
Davide Zambrano
S. Bohté
60
43
0
07 Sep 2016
Ternary Neural Networks for Resource-Efficient AI Applications
Ternary Neural Networks for Resource-Efficient AI Applications
Hande Alemdar
V. Leroy
Adrien Prost-Boucle
F. Pétrot
103
204
0
01 Sep 2016
Training Deep Spiking Neural Networks using Backpropagation
Training Deep Spiking Neural Networks using Backpropagation
Junhaeng Lee
T. Delbruck
Michael Pfeiffer
126
955
0
31 Aug 2016
Structured Convolution Matrices for Energy-efficient Deep learning
Structured Convolution Matrices for Energy-efficient Deep learning
R. Appuswamy
T. Nayak
John V. Arthur
S. K. Esser
P. Merolla
J. McKinstry
T. Melano
M. Flickner
D. Modha
55
11
0
08 Jun 2016
Deep neural networks are robust to weight binarization and other
  non-linear distortions
Deep neural networks are robust to weight binarization and other non-linear distortions
P. Merolla
R. Appuswamy
John V. Arthur
S. K. Esser
D. Modha
OODMQ
94
96
0
07 Jun 2016
Improving energy efficiency and classification accuracy of neuromorphic
  chips by learning binary synaptic crossbars
Improving energy efficiency and classification accuracy of neuromorphic chips by learning binary synaptic crossbars
Antonio Jimeno Yepes
Jianbin Tang
25
1
0
25 May 2016
Ternary Weight Networks
Ternary Weight Networks
Fengfu Li
Bin Liu
Xiaoxing Wang
Bo Zhang
Junchi Yan
MQ
101
527
0
16 May 2016
EIE: Efficient Inference Engine on Compressed Deep Neural Network
EIE: Efficient Inference Engine on Compressed Deep Neural Network
Song Han
Xingyu Liu
Huizi Mao
Jing Pu
A. Pedram
M. Horowitz
W. Dally
183
2,468
0
04 Feb 2016
Conversion of Artificial Recurrent Neural Networks to Spiking Neural
  Networks for Low-power Neuromorphic Hardware
Conversion of Artificial Recurrent Neural Networks to Spiking Neural Networks for Low-power Neuromorphic Hardware
P. U. Diehl
Guido Zarrella
A. Cassidy
Bruno U. Pedroni
Emre Neftci
92
219
0
16 Jan 2016
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