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Generating Visual Explanations

Generating Visual Explanations

28 March 2016
Lisa Anne Hendricks
Zeynep Akata
Marcus Rohrbach
Jeff Donahue
Bernt Schiele
Trevor Darrell
    VLM
    FAtt
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Papers citing "Generating Visual Explanations"

38 / 88 papers shown
Title
Drug discovery with explainable artificial intelligence
Drug discovery with explainable artificial intelligence
José Jiménez-Luna
F. Grisoni
G. Schneider
27
625
0
01 Jul 2020
A generalizable saliency map-based interpretation of model outcome
A generalizable saliency map-based interpretation of model outcome
Shailja Thakur
S. Fischmeister
AAML
FAtt
MILM
19
2
0
16 Jun 2020
AI Research Considerations for Human Existential Safety (ARCHES)
AI Research Considerations for Human Existential Safety (ARCHES)
Andrew Critch
David M. Krueger
22
50
0
30 May 2020
Explainable Deep Learning: A Field Guide for the Uninitiated
Explainable Deep Learning: A Field Guide for the Uninitiated
Gabrielle Ras
Ning Xie
Marcel van Gerven
Derek Doran
AAML
XAI
29
371
0
30 Apr 2020
Learning Global Transparent Models Consistent with Local Contrastive
  Explanations
Learning Global Transparent Models Consistent with Local Contrastive Explanations
Tejaswini Pedapati
Avinash Balakrishnan
Karthikeyan Shanmugam
Amit Dhurandhar
FAtt
15
0
0
19 Feb 2020
Evaluating Saliency Map Explanations for Convolutional Neural Networks:
  A User Study
Evaluating Saliency Map Explanations for Convolutional Neural Networks: A User Study
Ahmed Alqaraawi
M. Schuessler
Philipp Weiß
Enrico Costanza
N. Bianchi-Berthouze
AAML
FAtt
XAI
22
197
0
03 Feb 2020
CheXplain: Enabling Physicians to Explore and UnderstandData-Driven,
  AI-Enabled Medical Imaging Analysis
CheXplain: Enabling Physicians to Explore and UnderstandData-Driven, AI-Enabled Medical Imaging Analysis
Yao Xie
Melody Chen
David Kao
Ge Gao
Xiang Ánthony' Chen
28
125
0
15 Jan 2020
Keeping Community in the Loop: Understanding Wikipedia Stakeholder
  Values for Machine Learning-Based Systems
Keeping Community in the Loop: Understanding Wikipedia Stakeholder Values for Machine Learning-Based Systems
C. E. Smith
Bowen Yu
Anjali Srivastava
Aaron L Halfaker
Loren G. Terveen
Haiyi Zhu
KELM
14
69
0
14 Jan 2020
On the Explanation of Machine Learning Predictions in Clinical Gait
  Analysis
On the Explanation of Machine Learning Predictions in Clinical Gait Analysis
D. Slijepcevic
Fabian Horst
Sebastian Lapuschkin
Anna-Maria Raberger
Matthias Zeppelzauer
Wojciech Samek
C. Breiteneder
W. Schöllhorn
B. Horsak
22
50
0
16 Dec 2019
TAB-VCR: Tags and Attributes based Visual Commonsense Reasoning
  Baselines
TAB-VCR: Tags and Attributes based Visual Commonsense Reasoning Baselines
Jingxiang Lin
Unnat Jain
A. Schwing
LRM
ReLM
31
9
0
31 Oct 2019
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies,
  Opportunities and Challenges toward Responsible AI
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI
Alejandro Barredo Arrieta
Natalia Díaz Rodríguez
Javier Del Ser
Adrien Bennetot
S. Tabik
...
S. Gil-Lopez
Daniel Molina
Richard Benjamins
Raja Chatila
Francisco Herrera
XAI
37
6,109
0
22 Oct 2019
X-ToM: Explaining with Theory-of-Mind for Gaining Justified Human Trust
X-ToM: Explaining with Theory-of-Mind for Gaining Justified Human Trust
Arjun Reddy Akula
Changsong Liu
Sari Saba-Sadiya
Hongjing Lu
S. Todorovic
J. Chai
Song-Chun Zhu
19
18
0
15 Sep 2019
Explainability in Human-Agent Systems
Explainability in Human-Agent Systems
A. Rosenfeld
A. Richardson
XAI
21
203
0
17 Apr 2019
f-VAEGAN-D2: A Feature Generating Framework for Any-Shot Learning
f-VAEGAN-D2: A Feature Generating Framework for Any-Shot Learning
Yongqin Xian
Saurabh Sharma
Bernt Schiele
Zeynep Akata
GAN
VLM
16
482
0
25 Mar 2019
Generating Natural Language Explanations for Visual Question Answering
  using Scene Graphs and Visual Attention
Generating Natural Language Explanations for Visual Question Answering using Scene Graphs and Visual Attention
Shalini Ghosh
Giedrius Burachas
Arijit Ray
Avi Ziskind
11
65
0
15 Feb 2019
Learning to Explain with Complemental Examples
Learning to Explain with Complemental Examples
Atsushi Kanehira
Tatsuya Harada
10
40
0
04 Dec 2018
Multimodal Explanations by Predicting Counterfactuality in Videos
Multimodal Explanations by Predicting Counterfactuality in Videos
Atsushi Kanehira
Kentaro Takemoto
S. Inayoshi
Tatsuya Harada
18
35
0
04 Dec 2018
Understanding the Origins of Bias in Word Embeddings
Understanding the Origins of Bias in Word Embeddings
Marc-Etienne Brunet
Colleen Alkalay-Houlihan
Ashton Anderson
R. Zemel
FaML
13
198
0
08 Oct 2018
Faithful Multimodal Explanation for Visual Question Answering
Faithful Multimodal Explanation for Visual Question Answering
Jialin Wu
Raymond J. Mooney
11
90
0
08 Sep 2018
Interpretable to Whom? A Role-based Model for Analyzing Interpretable
  Machine Learning Systems
Interpretable to Whom? A Role-based Model for Analyzing Interpretable Machine Learning Systems
Richard J. Tomsett
Dave Braines
Daniel Harborne
Alun D. Preece
Supriyo Chakraborty
FaML
21
164
0
20 Jun 2018
Contrastive Explanations with Local Foil Trees
Contrastive Explanations with Local Foil Trees
J. V. D. Waa
M. Robeer
J. Diggelen
Matthieu J. S. Brinkhuis
Mark Antonius Neerincx
FAtt
14
82
0
19 Jun 2018
RISE: Randomized Input Sampling for Explanation of Black-box Models
RISE: Randomized Input Sampling for Explanation of Black-box Models
Vitali Petsiuk
Abir Das
Kate Saenko
FAtt
14
1,149
0
19 Jun 2018
Explaining Explanations: An Overview of Interpretability of Machine
  Learning
Explaining Explanations: An Overview of Interpretability of Machine Learning
Leilani H. Gilpin
David Bau
Ben Z. Yuan
Ayesha Bajwa
Michael A. Specter
Lalana Kagal
XAI
38
1,840
0
31 May 2018
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust
  Deep Learning
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning
Nicolas Papernot
Patrick D. McDaniel
OOD
AAML
8
502
0
13 Mar 2018
Discriminability objective for training descriptive captions
Discriminability objective for training descriptive captions
Ruotian Luo
Brian L. Price
Scott D. Cohen
Gregory Shakhnarovich
19
202
0
12 Mar 2018
The Challenge of Crafting Intelligible Intelligence
The Challenge of Crafting Intelligible Intelligence
Daniel S. Weld
Gagan Bansal
15
241
0
09 Mar 2018
Teaching Categories to Human Learners with Visual Explanations
Teaching Categories to Human Learners with Visual Explanations
Oisin Mac Aodha
Shihan Su
Yuxin Chen
Pietro Perona
Yisong Yue
10
70
0
20 Feb 2018
Multimodal Explanations: Justifying Decisions and Pointing to the
  Evidence
Multimodal Explanations: Justifying Decisions and Pointing to the Evidence
Dong Huk Park
Lisa Anne Hendricks
Zeynep Akata
Anna Rohrbach
Bernt Schiele
Trevor Darrell
Marcus Rohrbach
35
418
0
15 Feb 2018
What do we need to build explainable AI systems for the medical domain?
What do we need to build explainable AI systems for the medical domain?
Andreas Holzinger
Chris Biemann
C. Pattichis
D. Kell
28
680
0
28 Dec 2017
Inverse Classification for Comparison-based Interpretability in Machine
  Learning
Inverse Classification for Comparison-based Interpretability in Machine Learning
Thibault Laugel
Marie-Jeanne Lesot
Christophe Marsala
X. Renard
Marcin Detyniecki
13
100
0
22 Dec 2017
Using Program Induction to Interpret Transition System Dynamics
Using Program Induction to Interpret Transition System Dynamics
Svetlin Penkov
S. Ramamoorthy
AI4CE
25
11
0
26 Jul 2017
Translating Neuralese
Translating Neuralese
Jacob Andreas
Anca Dragan
Dan Klein
23
58
0
23 Apr 2017
It Takes Two to Tango: Towards Theory of AI's Mind
It Takes Two to Tango: Towards Theory of AI's Mind
Arjun Chandrasekaran
Deshraj Yadav
Prithvijit Chattopadhyay
Viraj Prabhu
Devi Parikh
28
53
0
03 Apr 2017
Towards a Visual Privacy Advisor: Understanding and Predicting Privacy
  Risks in Images
Towards a Visual Privacy Advisor: Understanding and Predicting Privacy Risks in Images
Rakshith Shetty
Bernt Schiele
Mario Fritz
27
223
0
30 Mar 2017
Survey of the State of the Art in Natural Language Generation: Core
  tasks, applications and evaluation
Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation
Albert Gatt
E. Krahmer
LM&MA
ELM
21
809
0
29 Mar 2017
Attentive Explanations: Justifying Decisions and Pointing to the
  Evidence
Attentive Explanations: Justifying Decisions and Pointing to the Evidence
Dong Huk Park
Lisa Anne Hendricks
Zeynep Akata
Bernt Schiele
Trevor Darrell
Marcus Rohrbach
AAML
16
79
0
14 Dec 2016
Making the V in VQA Matter: Elevating the Role of Image Understanding in
  Visual Question Answering
Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answering
Yash Goyal
Tejas Khot
D. Summers-Stay
Dhruv Batra
Devi Parikh
CoGe
99
3,116
0
02 Dec 2016
Learning Deep Representations of Fine-grained Visual Descriptions
Learning Deep Representations of Fine-grained Visual Descriptions
Scott E. Reed
Zeynep Akata
Bernt Schiele
Honglak Lee
OCL
VLM
170
840
0
17 May 2016
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