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Knowledge Consistency between Neural Networks and Beyond

Knowledge Consistency between Neural Networks and Beyond

5 August 2019
Ruofan Liang
Tianlin Li
Longfei Li
Jingchao Wang
Quanshi Zhang
ArXivPDFHTML

Papers citing "Knowledge Consistency between Neural Networks and Beyond"

15 / 15 papers shown
Title
Net2Vec: Quantifying and Explaining how Concepts are Encoded by Filters
  in Deep Neural Networks
Net2Vec: Quantifying and Explaining how Concepts are Encoded by Filters in Deep Neural Networks
Ruth C. Fong
Andrea Vedaldi
FAtt
58
263
0
10 Jan 2018
Apprentice: Using Knowledge Distillation Techniques To Improve
  Low-Precision Network Accuracy
Apprentice: Using Knowledge Distillation Techniques To Improve Low-Precision Network Accuracy
Asit K. Mishra
Debbie Marr
FedML
63
330
0
15 Nov 2017
Dynamic Routing Between Capsules
Dynamic Routing Between Capsules
S. Sabour
Nicholas Frosst
Geoffrey E. Hinton
117
4,584
0
26 Oct 2017
Interpretable Convolutional Neural Networks
Interpretable Convolutional Neural Networks
Quanshi Zhang
Ying Nian Wu
Song-Chun Zhu
FAtt
52
778
0
02 Oct 2017
A Closer Look at Memorization in Deep Networks
A Closer Look at Memorization in Deep Networks
Devansh Arpit
Stanislaw Jastrzebski
Nicolas Ballas
David M. Krueger
Emmanuel Bengio
...
Tegan Maharaj
Asja Fischer
Aaron Courville
Yoshua Bengio
Simon Lacoste-Julien
TDI
112
1,801
0
16 Jun 2017
Information-theoretic analysis of generalization capability of learning
  algorithms
Information-theoretic analysis of generalization capability of learning algorithms
Aolin Xu
Maxim Raginsky
123
442
0
22 May 2017
Interpretable Explanations of Black Boxes by Meaningful Perturbation
Interpretable Explanations of Black Boxes by Meaningful Perturbation
Ruth C. Fong
Andrea Vedaldi
FAtt
AAML
60
1,514
0
11 Apr 2017
Understanding Black-box Predictions via Influence Functions
Understanding Black-box Predictions via Influence Functions
Pang Wei Koh
Percy Liang
TDI
147
2,854
0
14 Mar 2017
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained
  Quantization and Huffman Coding
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding
Song Han
Huizi Mao
W. Dally
3DGS
219
8,793
0
01 Oct 2015
Neural Activation Constellations: Unsupervised Part Model Discovery with
  Convolutional Networks
Neural Activation Constellations: Unsupervised Part Model Discovery with Convolutional Networks
Marcel Simon
E. Rodner
59
412
0
30 Apr 2015
Object Detectors Emerge in Deep Scene CNNs
Object Detectors Emerge in Deep Scene CNNs
Bolei Zhou
A. Khosla
Àgata Lapedriza
A. Oliva
Antonio Torralba
ObjD
133
1,279
0
22 Dec 2014
Understanding Deep Image Representations by Inverting Them
Understanding Deep Image Representations by Inverting Them
Aravindh Mahendran
Andrea Vedaldi
FAtt
99
1,959
0
26 Nov 2014
How transferable are features in deep neural networks?
How transferable are features in deep neural networks?
J. Yosinski
Jeff Clune
Yoshua Bengio
Hod Lipson
OOD
169
8,309
0
06 Nov 2014
Visualizing and Understanding Convolutional Networks
Visualizing and Understanding Convolutional Networks
Matthew D. Zeiler
Rob Fergus
FAtt
SSL
389
15,825
0
12 Nov 2013
Representation Learning: A Review and New Perspectives
Representation Learning: A Review and New Perspectives
Yoshua Bengio
Aaron Courville
Pascal Vincent
OOD
SSL
192
12,384
0
24 Jun 2012
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