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1908.00085
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Why Does My Model Fail? Contrastive Local Explanations for Retail Forecasting
17 July 2019
Ana Lucic
H. Haned
Maarten de Rijke
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Papers citing
"Why Does My Model Fail? Contrastive Local Explanations for Retail Forecasting"
35 / 35 papers shown
Looking in the mirror: A faithful counterfactual explanation method for interpreting deep image classification models
T. Chowdhury
Vu Minh Hieu Phan
Kewen Liao
Nanyu Dong
Minh-Son To
Anton van den Hengel
Johan Verjans
Zhibin Liao
OOD
193
1
0
20 Sep 2025
Towards Human-centered Design of Explainable Artificial Intelligence (XAI): A Survey of Empirical Studies
Shuai Ma
320
6
0
28 Oct 2024
Good Data Is All Imitation Learning Needs
Amir Samadi
K. Koufos
Kurt Debattista
M. Dianati
OffRL
282
4
0
26 Sep 2024
Incremental XAI: Memorable Understanding of AI with Incremental Explanations
International Conference on Human Factors in Computing Systems (CHI), 2024
Jessica Y. Bo
Pan Hao
Brian Y Lim
CLL
249
20
0
10 Apr 2024
OpenHEXAI: An Open-Source Framework for Human-Centered Evaluation of Explainable Machine Learning
Jiaqi Ma
Vivian Lai
Yiming Zhang
Chacha Chen
Paul Hamilton
Davor Ljubenkov
Himabindu Lakkaraju
Chenhao Tan
ELM
209
5
0
20 Feb 2024
Decoding AI's Nudge: A Unified Framework to Predict Human Behavior in AI-assisted Decision Making
AAAI Conference on Artificial Intelligence (AAAI), 2024
Zhuoyan Li
Zhuoran Lu
Ming Yin
249
23
0
11 Jan 2024
Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions
Information Fusion (Inf. Fusion), 2023
Luca Longo
Mario Brcic
Federico Cabitza
Jaesik Choi
Roberto Confalonieri
...
Andrés Páez
Wojciech Samek
Johannes Schneider
Timo Speith
Simone Stumpf
555
436
0
30 Oct 2023
Counterfactual Explainer Framework for Deep Reinforcement Learning Models Using Policy Distillation
Amir Samadi
K. Koufos
Kurt Debattista
M. Dianati
OffRL
303
3
0
25 May 2023
Explaining Groups of Instances Counterfactually for XAI: A Use Case, Algorithm and User Study for Group-Counterfactuals
Greta Warren
Markt. Keane
Christophe Guéret
Eoin Delaney
218
15
0
16 Mar 2023
Selective Explanations: Leveraging Human Input to Align Explainable AI
Vivian Lai
Yiming Zhang
Chacha Chen
Q. V. Liao
Chenhao Tan
411
69
0
23 Jan 2023
Counterfactual Explanations for Misclassified Images: How Human and Machine Explanations Differ
Artificial Intelligence (AI), 2022
Eoin Delaney
A. Pakrashi
Derek Greene
Markt. Keane
301
24
0
16 Dec 2022
A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation, and Research Challenges
ACM Computing Surveys (ACM CSUR), 2022
Mario Alfonso Prado-Romero
Bardh Prenkaj
Giovanni Stilo
F. Giannotti
CML
318
46
0
21 Oct 2022
Anomaly Attribution with Likelihood Compensation
AAAI Conference on Artificial Intelligence (AAAI), 2021
T. Idé
Amit Dhurandhar
Jirí Navrátil
Moninder Singh
Naoki Abe
130
16
0
23 Aug 2022
Connecting Algorithmic Research and Usage Contexts: A Perspective of Contextualized Evaluation for Explainable AI
AAAI Conference on Human Computation & Crowdsourcing (HCOMP), 2022
Q. V. Liao
Yunfeng Zhang
Ronny Luss
Finale Doshi-Velez
Amit Dhurandhar
343
94
0
22 Jun 2022
Causal Explanations for Sequential Decision Making Under Uncertainty
Adaptive Agents and Multi-Agent Systems (AAMAS), 2022
Samer B. Nashed
Saaduddin Mahmud
C. V. Goldman
S. Zilberstein
CML
311
4
0
30 May 2022
Justifying Social-Choice Mechanism Outcome for Improving Participant Satisfaction
Adaptive Agents and Multi-Agent Systems (AAMAS), 2022
Sharadhi Alape Suryanarayana
David Sarne
Bar-Ilan
321
9
0
24 May 2022
Can counterfactual explanations of AI systems' predictions skew lay users' causal intuitions about the world? If so, can we correct for that?
Patterns (Patterns), 2022
Marko Tešić
U. Hahn
CML
178
7
0
12 May 2022
Interactive Model Cards: A Human-Centered Approach to Model Documentation
Conference on Fairness, Accountability and Transparency (FAccT), 2022
Anamaria Crisan
Margaret Drouhard
Jesse Vig
Nazneen Rajani
HAI
276
126
0
05 May 2022
The Value of Measuring Trust in AI - A Socio-Technical System Perspective
Michaela Benk
Suzanne Tolmeijer
F. Wangenheim
Andrea Ferrario
115
17
0
28 Apr 2022
Features of Explainability: How users understand counterfactual and causal explanations for categorical and continuous features in XAI
Greta Warren
Mark T. Keane
R. Byrne
CML
172
30
0
21 Apr 2022
Benchmarking Instance-Centric Counterfactual Algorithms for XAI: From White Box to Black Box
ACM Computing Surveys (ACM CSUR), 2022
Catarina Moreira
Yu-Liang Chou
Chih-Jou Hsieh
Chun Ouyang
Joaquim A. Jorge
João Pereira
CML
452
13
0
04 Mar 2022
Machine Explanations and Human Understanding
Chacha Chen
Shi Feng
Amit Sharma
Chenhao Tan
398
33
0
08 Feb 2022
Towards a Science of Human-AI Decision Making: A Survey of Empirical Studies
Vivian Lai
Chacha Chen
Q. V. Liao
Alison Smith-Renner
Chenhao Tan
339
224
0
21 Dec 2021
Human-Centered Explainable AI (XAI): From Algorithms to User Experiences
Q. V. Liao
R. Varshney
651
303
0
20 Oct 2021
Uncertainty Estimation and Out-of-Distribution Detection for Counterfactual Explanations: Pitfalls and Solutions
Eoin Delaney
Derek Greene
Mark T. Keane
246
29
0
20 Jul 2021
How Well do Feature Visualizations Support Causal Understanding of CNN Activations?
Roland S. Zimmermann
Judy Borowski
Robert Geirhos
Matthias Bethge
Thomas S. A. Wallis
Wieland Brendel
FAtt
368
42
0
23 Jun 2021
To Trust or Not to Trust a Regressor: Estimating and Explaining Trustworthiness of Regression Predictions
K. D. Bie
Ana Lucic
H. Haned
FAtt
165
12
0
14 Apr 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
428
226
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
355
170
0
26 Feb 2021
Benchmarking and Survey of Explanation Methods for Black Box Models
Data mining and knowledge discovery (DMKD), 2021
F. Bodria
F. Giannotti
Riccardo Guidotti
Francesca Naretto
D. Pedreschi
S. Rinzivillo
XAI
495
304
0
25 Feb 2021
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Ana Lucic
Maartje ter Hoeve
Gabriele Tolomei
Maarten de Rijke
Fabrizio Silvestri
633
180
0
05 Feb 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
781
274
0
20 Oct 2020
A survey of algorithmic recourse: definitions, formulations, solutions, and prospects
Amir-Hossein Karimi
Gilles Barthe
Bernhard Schölkopf
Isabel Valera
FaML
405
186
0
08 Oct 2020
On Generating Plausible Counterfactual and Semi-Factual Explanations for Deep Learning
AAAI Conference on Artificial Intelligence (AAAI), 2020
Eoin M. Kenny
Mark T. Keane
290
117
0
10 Sep 2020
A Bandit Model for Human-Machine Decision Making with Private Information and Opacity
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Sebastian Bordt
U. V. Luxburg
422
10
0
09 Jul 2020
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