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2008.08353
Cited By
DECE: Decision Explorer with Counterfactual Explanations for Machine Learning Models
19 August 2020
Furui Cheng
Yao Ming
Huamin Qu
CML
HAI
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Papers citing
"DECE: Decision Explorer with Counterfactual Explanations for Machine Learning Models"
49 / 49 papers shown
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Visualizing Spatial Semantics of Dimensionally Reduced Text Embeddings
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144
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Beyond Correlation: Incorporating Counterfactual Guidance to Better Support Exploratory Visual Analysis
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Arran Zeyu Wang
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David Gotz
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244
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28 Aug 2024
Interactive Counterfactual Generation for Univariate Time Series
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Julius Rauscher
Daniel A. Keim
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250
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CausalPrism: A Visual Analytics Approach for Subgroup-based Causal Heterogeneity Exploration
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Xumeng Wang
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Wei Zhang
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Wei Chen
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231
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02 Jul 2024
MiMICRI: Towards Domain-centered Counterfactual Explanations of Cardiovascular Image Classification Models
G. Guo
Lifu Deng
A. Tandon
Alex Endert
Bum Chul Kwon
289
6
0
24 Apr 2024
Understanding Large Language Model Behaviors through Interactive Counterfactual Generation and Analysis
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Vilém Zouhar
Robin Shing Moon Chan
Daniel Fürst
Hendrik Strobelt
Mennatallah El-Assady
499
11
0
23 Apr 2024
Enhancing Counterfactual Explanation Search with Diffusion Distance and Directional Coherence
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Raul Vicente
213
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19 Apr 2024
JailbreakLens: Visual Analysis of Jailbreak Attacks Against Large Language Models
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Zhizhang Chen
Zhining Kang
Sijia Wang
Haoyu Tian
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Minfeng Zhu
Wei Chen
340
8
0
12 Apr 2024
Exploiting Preference Elicitation in Interactive and User-centered Algorithmic Recourse: An Initial Exploration
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Giovanni De Toni
Bruno Lepri
Baptiste Caramiaux
Katya Tentori
Massimo Zancanaro
261
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08 Apr 2024
Sparse and Faithful Explanations Without Sparse Models
Yiyang Sun
Zhi Chen
Vittorio Orlandi
Tong Wang
Cynthia Rudin
295
4
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15 Feb 2024
Distributional Counterfactual Explanations With Optimal Transport
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Lei You
Lele Cao
Mattias Nilsson
Bo Zhao
Lei Lei
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577
1
0
23 Jan 2024
An Empirical Study of Counterfactual Visualization to Support Visual Causal Inference
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Arran Zeyu Wang
D. Borland
David Gotz
CML
231
15
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16 Jan 2024
Model-Agnostic Interpretation Framework in Machine Learning: A Comparative Study in NBA Sports
Shun Liu
183
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05 Jan 2024
T-COL: Generating Counterfactual Explanations for General User Preferences on Variable Machine Learning Systems
Yiming Li
Daling Wang
Wenfang Wu
Shi Feng
Yifei Zhang
CML
238
1
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28 Sep 2023
Flexible and Robust Counterfactual Explanations with Minimal Satisfiable Perturbations
International Conference on Information and Knowledge Management (CIKM), 2023
Yongjie Wang
Hangwei Qian
Yongjie Liu
Wei Guo
Chunyan Miao
229
6
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09 Sep 2023
Towards User Guided Actionable Recourse
AAAI/ACM Conference on AI, Ethics, and Society (AIES), 2023
Jayanth Yetukuri
Ian Hardy
Yang Liu
193
4
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05 Sep 2023
Prediction without Preclusion: Recourse Verification with Reachable Sets
International Conference on Learning Representations (ICLR), 2023
Avni Kothari
B. Kulynych
Tsui-Wei Weng
Berk Ustun
FaML
275
7
0
24 Aug 2023
Are We Closing the Loop Yet? Gaps in the Generalizability of VIS4ML Research
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2023
Hariharan Subramonyam
Jessica Hullman
VLM
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151
12
0
10 Aug 2023
VISPUR: Visual Aids for Identifying and Interpreting Spurious Associations in Data-Driven Decisions
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2023
Xian Teng
Yongsu Ahn
Y. Lin
CML
190
5
0
26 Jul 2023
TimeTuner: Diagnosing Time Representations for Time-Series Forecasting with Counterfactual Explanations
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2023
Jianing Hao
Qing Shi
Yilin Ye
Weizhen Zeng
AI4TS
307
10
0
19 Jul 2023
Visual Analytics For Machine Learning: A Data Perspective Survey
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2023
Junpeng Wang
Shixia Liu
Wei Zhang
HAI
224
35
0
15 Jul 2023
Calculating and Visualizing Counterfactual Feature Importance Values
B. Meulemeester
Raphael Mazzine Barbosa de Oliveira
David Martens
FAtt
95
4
0
10 Jun 2023
Achieving Diversity in Counterfactual Explanations: a Review and Discussion
Conference on Fairness, Accountability and Transparency (FAccT), 2023
Thibault Laugel
Adulam Jeyasothy
Marie-Jeanne Lesot
Christophe Marsala
Marcin Detyniecki
CML
185
16
0
10 May 2023
Towards an Understanding and Explanation for Mixed-Initiative Artificial Scientific Text Detection
Information Visualization (InfoVis), 2023
Luoxuan Weng
Minfeng Zhu
Kamkwai Wong
Siyi Liu
Jiashun Sun
Hang Zhu
Dongming Han
Wei Chen
DeLMO
224
10
0
11 Apr 2023
DASS Good: Explainable Data Mining of Spatial Cohort Data
A. Wentzel
Carla Floricel
G. Canahuate
Mohamed A.Naser
A. Mohamed
Clifton Fuller
L. V. Dijk
G. Marai
OOD
154
10
0
10 Apr 2023
GAM Coach: Towards Interactive and User-centered Algorithmic Recourse
International Conference on Human Factors in Computing Systems (CHI), 2023
Zijie J. Wang
J. W. Vaughan
R. Caruana
Duen Horng Chau
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340
26
0
27 Feb 2023
DendroMap: Visual Exploration of Large-Scale Image Datasets for Machine Learning with Treemaps
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2022
Donald Bertucci
M. Hamid
Yashwanthi Anand
Anita Ruangrotsakun
Delyar Tabatabai
Melissa Perez
Minsuk Kahng
216
35
0
14 May 2022
IF-City: Intelligible Fair City Planning to Measure, Explain and Mitigate Inequality
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2022
Yan Lyu
Hangxin Lu
Min Kyung Lee
G. Schmitt
Brian Y. Lim
137
20
0
15 Feb 2022
In Defence of Visual Analytics Systems: Replies to Critics
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2022
Aoyu Wu
Dazhen Deng
Furui Cheng
Yingcai Wu
Shixia Liu
Huamin Qu
AAML
HAI
405
27
0
24 Jan 2022
Visual Identification of Problematic Bias in Large Label Spaces
Alex Bauerle
Aybuke Turker
Ken Burke
Osman Aka
Timo Ropinski
Christina Greer
Mani Varadarajan
154
2
0
17 Jan 2022
Fighting Money Laundering with Statistics and Machine Learning
IEEE Access (IEEE Access), 2022
R. Jensen
Alexandros Iosifidis
371
27
0
11 Jan 2022
Low-Cost Algorithmic Recourse for Users With Uncertain Cost Functions
Prateek Yadav
Peter Hase
Joey Tianyi Zhou
204
12
0
01 Nov 2021
Augmenting Decision Making via Interactive What-If Analysis
Sneha Gathani
Madelon Hulsebos
James Gale
P. Haas
cCaugatay Demiralp
266
11
0
13 Sep 2021
AdViCE: Aggregated Visual Counterfactual Explanations for Machine Learning Model Validation
Oscar Gomez
Steffen Holter
Jun Yuan
E. Bertini
AAML
CML
HAI
86
25
0
12 Sep 2021
VBridge: Connecting the Dots Between Features and Data to Explain Healthcare Models
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2021
Furui Cheng
Dongyu Liu
F. Du
Yanna Lin
Alexandra Zytek
Haomin Li
Huamin Qu
K. Veeramachaneni
132
49
0
04 Aug 2021
Improving Visualization Interpretation Using Counterfactuals
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2021
Smiti Kaul
D. Borland
Nan Cao
David Gotz
CML
121
24
0
21 Jul 2021
Why? Why not? When? Visual Explanations of Agent Behavior in Reinforcement Learning
IEEE Pacific Visualization Symposium (PacificVis), 2021
Aditi Mishra
Utkarsh Soni
Jinbin Huang
Chris Bryan
OffRL
163
27
0
06 Apr 2021
ECINN: Efficient Counterfactuals from Invertible Neural Networks
British Machine Vision Conference (BMVC), 2021
Frederik Hvilshoj
Alexandros Iosifidis
Ira Assent
BDL
203
32
0
25 Mar 2021
Counterfactual Explanation with Multi-Agent Reinforcement Learning for Drug Target Prediction
T. Nguyen
Thomas P. Quinn
Thin Nguyen
T. Tran
CML
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215
11
0
24 Mar 2021
Counterfactuals and Causability in Explainable Artificial Intelligence: Theory, Algorithms, and Applications
Information Fusion (Inf. Fusion), 2021
Yu-Liang Chou
Catarina Moreira
P. Bruza
Chun Ouyang
Joaquim A. Jorge
CML
382
220
0
07 Mar 2021
If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI Techniques
International Joint Conference on Artificial Intelligence (IJCAI), 2021
Mark T. Keane
Eoin M. Kenny
Eoin Delaney
Barry Smyth
CML
300
167
0
26 Feb 2021
Vis Ex Machina: An Analysis of Trust in Human versus Algorithmically Generated Visualization Recommendations
International Conference on Human Factors in Computing Systems (CHI), 2021
Rachael Zehrung
A. Singhal
M. Correll
Leilani Battle
HAI
120
23
0
12 Jan 2021
Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review
ACM Computing Surveys (ACM CSUR), 2020
Sahil Verma
Varich Boonsanong
Minh Hoang
Keegan E. Hines
John P. Dickerson
Chirag Shah
CML
718
251
0
20 Oct 2020
A survey of algorithmic recourse: definitions, formulations, solutions, and prospects
Amir-Hossein Karimi
Gilles Barthe
Bernhard Schölkopf
Isabel Valera
FaML
351
185
0
08 Oct 2020
SUBPLEX: Towards a Better Understanding of Black Box Model Explanations at the Subpopulation Level
Jun Yuan
Gromit Yeuk-Yin Chan
Brian Barr
Kyle Overton
Kim Rees
Luis Gustavo Nonato
Enrico Bertini
Claudio T. Silva
64
1
0
21 Jul 2020
PRINCE: Provider-side Interpretability with Counterfactual Explanations in Recommender Systems
Web Search and Data Mining (WSDM), 2019
Azin Ghazimatin
Oana Balalau
Rishiraj Saha Roy
Gerhard Weikum
FAtt
409
104
0
19 Nov 2019
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