Gary Klein

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All published works

Action	Title	Year	Authors
+	The Plausibility Gap: A model of sensemaking	2021	Gary Klein Mohammadreza Jalaeian Robert S. Hoffman Shane T. Mueller
+	Authoring Guide for Cognitive Tutorials for Artificial Intelligence: Purposes and Methods	2021	Shane T. Mueller Yin-Yin Tan Anne Linja Gary Klein Robert M. Hoffman
+	Principles of Explanation in Human-AI Systems.	2021	Shane T. Mueller Elizabeth S. Veinott Robert R. Hoffman Gary Klein Lamia Alam Tauseef Ibne Mamun William J. Clancey
+	Principles of Explanation in Human-AI Systems	2021	Shane T. Mueller Elizabeth S. Veinott Robert R. Hoffman Gary Klein Lamia Alam Tauseef Ibne Mamun William J. Clancey
+	Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI	2019	Shane T. Mueller Robert R. Hoffman William J. Clancey Abagail K. Emery Gary Klein
+	Metrics for Explainable AI: Challenges and Prospects.	2018	Robert R. Hoffman Shane T. Mueller Gary Klein Jordan A. Litman
+	Metrics for Explainable AI: Challenges and Prospects	2018	Robert R. Hoffman Shane T. Mueller Gary Klein Jordan A. Litman
+	Research Guides: Statistics - Education, Schools & Students: Home	2012	Gary Klein
+	Comparison-Based Predictions and Recommendations for Army Maintenance Training Devices	1985	Gary Klein Sallie E. Gordon Mark Palmisano Angelo Mirabella
+	Curriculum Development versus Education	1983	Gary Klein

Common Coauthors

Coauthor	Papers Together
Shane T. Mueller	7
Robert R. Hoffman	5
William J. Clancey	3
Lamia Alam	2
Jordan A. Litman	2
Tauseef Ibne Mamun	2
Elizabeth S. Veinott	2
Abagail K. Emery	1
Yin-Yin Tan	1
Angelo Mirabella	1
Sallie E. Gordon	1
Robert S. Hoffman	1
Robert M. Hoffman	1
Anne Linja	1
Mark Palmisano	1
Mohammadreza Jalaeian	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Explanation in Artificial Intelligence: Insights from the Social Sciences	2017	Tim Miller	2
+ PDF Chat	Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization	2017	Ramprasaath R. Selvaraju Michael Cogswell Abhishek Das Ramakrishna Vedantam Devi Parikh Dhruv Batra	2
+	Explanation in artificial intelligence: Insights from the social sciences	2018	Tim Miller	2
+	Interpretable and Explorable Approximations of Black Box Models	2017	Himabindu Lakkaraju Ece Kamar Rich Caruana Jure Leskovec	2
+ PDF Chat	European Union Regulations on Algorithmic Decision Making and a “Right to Explanation”	2017	Bryce Goodman Seth Flaxman	2
+	Towards A Rigorous Science of Interpretable Machine Learning	2017	Finale Doshi‐Velez Been Kim	2
+	What is coefficient alpha? An examination of theory and applications.	1993	José M. Cortina	1
+	Promoting Active Learning	2013	Jennifer A. Strangfeld	1
+ PDF Chat	Label-Embedding for Image Classification	2015	Zeynep Akata Florent Perronnin Zaïd Harchaoui Cordelia Schmid	1
+ PDF Chat	Generating Visual Explanations	2016	Lisa Anne Hendricks Zeynep Akata Marcus Rohrbach Jeff Donahue Bernt Schiele Trevor Darrell	1
+	Toward a general, scaleable framework for Bayesian teaching with applications to topic models	2016	Baxter Eaves Patrick Shafto	1
+	Model-Agnostic Interpretability of Machine Learning	2016	Marco Túlio Ribeiro Sameer Singh Carlos Guestrin	1
+	Concrete Problems in AI Safety	2016	Dario Amodei Chris Olah Jacob Steinhardt Paul F. Christiano John Schulman Dan Mané	1
+	Explaining Classification Models Built on High-Dimensional Sparse Data	2016	Julie Moeyersoms B D'Alessandro Foster Provost David Martens	1
+	Interpreting Visual Question Answering Models.	2016	Yash Goyal Akrit Mohapatra Devi Parikh Dhruv Batra	1
+	Episodic Exploration for Deep Deterministic Policies: An Application to StarCraft Micromanagement Tasks	2016	Nicolas Usunier Gabriel Synnaeve Zeming Lin Soumith Chintala	1
+	Rawlsian Fairness for Machine Learning.	2016	Matthew Joseph Michael Kearns Jamie Morgenstern Seth Neel Aaron Roth	1
+ PDF Chat	Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answering	2017	Yash Goyal Tejas Khot Douglas Summers-Stay Dhruv Batra Devi Parikh	1
+	A Roadmap for a Rigorous Science of Interpretability.	2017	Finale Doshi‐Velez Been Kim	1
+	Opening the Black Box of Deep Neural Networks via Information	2017	Ravid Shwartz-Ziv Naftali Tishby	1
+	Understanding Black-box Predictions via Influence Functions	2017	Pang Wei Koh Percy Liang	1
+ PDF Chat	Explaining the Unexplained: A CLass-Enhanced Attentive Response (CLEAR) Approach to Understanding Deep Neural Networks	2017	Devinder Kumar Alexander Wong Graham W. Taylor	1
+	What Does Explainable AI Really Mean? A New Conceptualization of Perspectives	2017	Derek Doran Sarah Schulz Tarek R. Besold	1
+	Deep Learning: A Critical Appraisal	2018	Gary Marcus	1
+	How do Humans Understand Explanations from Machine Learning Systems? An Evaluation of the Human-Interpretability of Explanation.	2018	Menaka Narayanan Emily Chen Jeffrey He Been Kim Sam Gershman Finale Doshi‐Velez	1
+	Explainable artificial intelligence (XAI), the goodness criteria and the grasp-ability test.	2018	Tae Wan Kim	1
+	Metrics for Explainable AI: Challenges and Prospects.	2018	Robert R. Hoffman Shane T. Mueller Gary Klein Jordan A. Litman	1
+	Multi-Agent Cooperation and the Emergence of (Natural) Language	2016	Angeliki Lazaridou Alexander Peysakhovich Marco Baroni	1
+	"Why Should I Trust You?": Explaining the Predictions of Any Classifier	2016	Marco Túlio Ribeiro Sameer Singh Carlos Guestrin	1
+ PDF Chat	Towards Accountable AI: Hybrid Human-Machine Analyses for Characterizing System Failure	2018	Besmira Nushi Ece Kamar Eric Horvitz	1
+ PDF Chat	On Human Intellect and Machine Failures: Troubleshooting Integrative Machine Learning Systems	2017	Besmira Nushi Ece Kamar Eric Horvitz Donald Kossmann	1
+ PDF Chat	On the Safety of Machine Learning: Cyber-Physical Systems, Decision Sciences, and Data Products	2017	Kush R. Varshney Homa Alemzadeh	1
+	Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps	2013	Karen Simonyan Andrea Vedaldi Andrew Zisserman	1
+ PDF Chat	Learning to Reason: End-to-End Module Networks for Visual Question Answering	2017	Ronghang Hu Jacob Andreas Marcus Rohrbach Trevor Darrell Kate Saenko	1
+ PDF Chat	Rationalizing Neural Predictions	2016	Tao Leí Regina Barzilay Tommi Jaakkola	1
+	Striving for Simplicity: The All Convolutional Net	2014	Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller	1
+ PDF Chat	Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding	2016	Akira Fukui Dong Huk Park Daylen Yang Anna Rohrbach Trevor Darrell Marcus Rohrbach	1
+	Natural Language Generation enhances human decision-making with uncertain information	2016	Dimitra Gkatzia Oliver Lemon Verena Rieser	1
+	Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations	2017	Andrew Slavin Ross Michael C. Hughes Finale Doshi‐Velez	1
+ PDF Chat	Explaining Explanations: An Overview of Interpretability of Machine Learning	2018	Leilani H. Gilpin David Bau Ben Z. Yuan Ayesha Bajwa Michael A. Specter Lalana Kagal	1
+	A note on the evaluation of generative models	2015	Lucas Theis Aäron van den Oord Matthias Bethge	1
+ PDF Chat	Visualizing and Understanding Neural Models in NLP	2016	Jiwei Li Xinlei Chen Eduard Hovy Dan Jurafsky	1
+ PDF Chat	On Generating Plausible Counterfactual and Semi-Factual Explanations for Deep Learning	2021	Eoin M. Kenny Mark T. Keane	1
+ PDF Chat	A Survey on Bayesian Deep Learning	2020	Hao Wang Dit‐Yan Yeung	1
+	Explaining AI as an Exploratory Process: The Peircean Abduction Model	2020	Robert R. Hoffman William J. Clancey Shane T. Mueller	1
+ PDF Chat	Accountability of AI Under the Law: The Role of Explanation	2017	Finale Doshi‐Velez Mason A. Kortz Ryan Budish Christopher Bavitz Samuel J. Gershman David F. O’Brien Kate Scott Stuart M. Shieber Jim Waldo David Weinberger	1
+	Principles of Explanation in Human-AI Systems	2021	Shane T. Mueller Elizabeth S. Veinott Robert R. Hoffman Gary Klein Lamia Alam Tauseef Ibne Mamun William J. Clancey	1
+	Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks	2015	Jason Weston Antoine Bordes Sumit Chopra Alexander M. Rush Bart van Merriënboer Armand Joulin Tomáš Mikolov	1
+	On the Robustness of Most Probable Explanations	2012	Hei Chan Adnan Darwiche	1
+	Distilling the Knowledge in a Neural Network	2015	Geoffrey E. Hinton Oriol Vinyals Jay B. Dean	1