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Visual Summary of Value-level Feature Attribution in Prediction Classes
  with Recurrent Neural Networks

Visual Summary of Value-level Feature Attribution in Prediction Classes with Recurrent Neural Networks

23 January 2020
Chuan-Chi Wang
Xumeng Wang
K. Ma
    FAtt
    HAI
ArXivPDFHTML

Papers citing "Visual Summary of Value-level Feature Attribution in Prediction Classes with Recurrent Neural Networks"

6 / 6 papers shown
Title
Interpretable and Steerable Sequence Learning via Prototypes
Interpretable and Steerable Sequence Learning via Prototypes
Yao Ming
Panpan Xu
Huamin Qu
Liu Ren
AI4TS
21
139
0
23 Jul 2019
RetainVis: Visual Analytics with Interpretable and Interactive Recurrent
  Neural Networks on Electronic Medical Records
RetainVis: Visual Analytics with Interpretable and Interactive Recurrent Neural Networks on Electronic Medical Records
Bum Chul Kwon
Min-Je Choi
J. Kim
Edward Choi
Young Bin Kim
Soonwook Kwon
Jimeng Sun
Jaegul Choo
62
252
0
28 May 2018
Learning Important Features Through Propagating Activation Differences
Learning Important Features Through Propagating Activation Differences
Avanti Shrikumar
Peyton Greenside
A. Kundaje
FAtt
123
3,848
0
10 Apr 2017
Not Just a Black Box: Learning Important Features Through Propagating
  Activation Differences
Not Just a Black Box: Learning Important Features Through Propagating Activation Differences
Avanti Shrikumar
Peyton Greenside
A. Shcherbina
A. Kundaje
FAtt
56
782
0
05 May 2016
Visualizing and Understanding Recurrent Networks
Visualizing and Understanding Recurrent Networks
A. Karpathy
Justin Johnson
Li Fei-Fei
HAI
81
1,100
0
05 Jun 2015
Show, Attend and Tell: Neural Image Caption Generation with Visual
  Attention
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
Ke Xu
Jimmy Ba
Ryan Kiros
Kyunghyun Cho
Aaron Courville
Ruslan Salakhutdinov
R. Zemel
Yoshua Bengio
DiffM
279
10,034
0
10 Feb 2015
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