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1801.06889
Cited By
Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers
21 January 2018
Fred Hohman
Minsuk Kahng
Robert S. Pienta
Duen Horng Chau
OOD
HAI
Re-assign community
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Papers citing
"Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers"
13 / 63 papers shown
Title
LassoNet: Deep Lasso-Selection of 3D Point Clouds
Zhutian Chen
Wei Zeng
Zhiguang Yang
Lingyun Yu
Chi-Wing Fu
Huamin Qu
3DPC
18
44
0
31 Jul 2019
Visual Interaction with Deep Learning Models through Collaborative Semantic Inference
Sebastian Gehrmann
Hendrik Strobelt
Robert Krüger
Hanspeter Pfister
Alexander M. Rush
HAI
18
57
0
24 Jul 2019
The Role of Cooperation in Responsible AI Development
Amanda Askell
Miles Brundage
Gillian Hadfield
17
59
0
10 Jul 2019
The What-If Tool: Interactive Probing of Machine Learning Models
James Wexler
Mahima Pushkarna
Tolga Bolukbasi
Martin Wattenberg
F. Viégas
Jimbo Wilson
VLM
32
485
0
09 Jul 2019
NNVA: Neural Network Assisted Visual Analysis of Yeast Cell Polarization Simulation
Subhashis Hazarika
Haoyu Li
Ko-Chih Wang
Han-Wei Shen
Ching-Shan Chou
23
20
0
19 Apr 2019
Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations
Fred Hohman
Haekyu Park
Caleb Robinson
Duen Horng Chau
FAtt
3DH
HAI
17
213
0
04 Apr 2019
VINE: Visualizing Statistical Interactions in Black Box Models
M. Britton
FAtt
14
21
0
01 Apr 2019
Robust Reference Frame Extraction from Unsteady 2D Vector Fields with Convolutional Neural Networks
Byungsoo Kim
Tobias Günther
3DPC
18
41
0
25 Mar 2019
A Gray Box Interpretable Visual Debugging Approach for Deep Sequence Learning Model
Md. Mofijul Islam
Amar Debnath
Tahsin Al Sayeed
Jyotirmay Nag Setu
Md Mahmudur Rahman
Md. Sadman Sakib
M. Razzaque
Md. Mosaddek Khan
Swakkhar Shatabda
HAI
AAML
VLM
14
0
0
20 Nov 2018
Seq2Seq-Vis: A Visual Debugging Tool for Sequence-to-Sequence Models
Hendrik Strobelt
Sebastian Gehrmann
M. Behrisch
Adam Perer
Hanspeter Pfister
Alexander M. Rush
VLM
HAI
28
239
0
25 Apr 2018
Shield: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression
Nilaksh Das
Madhuri Shanbhogue
Shang-Tse Chen
Fred Hohman
Siwei Li
Li-Wei Chen
Michael E. Kounavis
Duen Horng Chau
FedML
AAML
38
224
0
19 Feb 2018
Methods for Interpreting and Understanding Deep Neural Networks
G. Montavon
Wojciech Samek
K. Müller
FaML
234
2,238
0
24 Jun 2017
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
284
5,835
0
08 Jul 2016
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