Yan Zhou

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All published works

Action	Title	Year	Authors
+	GTHP: a novel graph transformer Hawkes process for spatiotemporal event prediction	2024	Yiman Xie Jianbin Wu Yan Zhou
+	Using AI Uncertainty Quantification to Improve Human Decision-Making	2023	Laura R. Marusich Jonathan Z. Bakdash Yan Zhou Murat Kantarcıoğlu
+	Using AI Uncertainty Quantification to Improve Human Decision-Making	2023	Laura R. Marusich Jonathan Z. Bakdash Yan Zhou Murat Kantarcıoğlu
+	Astrologer: Exploiting graph neural Hawkes process for event propagation prediction with spatio-temporal characteristics	2021	Haizhou Du Yan Zhou Yunpu Ma Shiwei Wang
+ PDF Chat	Does Explainable Artificial Intelligence Improve Human Decision-Making?	2021	Yasmeen Alufaisan Laura R. Marusich Jonathan Z. Bakdash Yan Zhou Murat Kantarcıoğlu
+	Improving Fairness of AI Systems with Lossless De-biasing	2021	Yan Zhou Murat Kantarcıoğlu Chris Clifton
+	Does Explainable Artificial Intelligence Improve Human Decision-Making?	2020	Yasmeen Alufaisan Laura R. Marusich Jonathan Z. Bakdash Yan Zhou Murat Kantarcıoğlu

Common Coauthors

Coauthor	Papers Together
Murat Kantarcıoğlu	5
Jonathan Z. Bakdash	4
Laura R. Marusich	4
Yasmeen Alufaisan	2
Chris Clifton	1
Jianbin Wu	1
Shiwei Wang	1
Haizhou Du	1
Yiman Xie	1
Yunpu Ma	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	Effect of confidence and explanation on accuracy and trust calibration in AI-assisted decision making	2020	Yunfeng Zhang Q. Vera Liao Rachel Bellamy	3
+	Identifying and labeling search tasks via query-based hawkes processes	2014	Liangda Li Hongbo Deng Anlei Dong Yi Chang Hongyuan Zha	2
+ PDF Chat	Dyadic event attribution in social networks with mixtures of hawkes processes	2013	Liangda Li Hongyuan Zha	2
+	Improving Maximum Likelihood Estimation of Temporal Point Process via Discriminative and Adversarial Learning	2018	Junchi Yan Xin Liu Liangliang Shi Changsheng Li Hongyuan Zha	2
+	The Measure and Mismeasure of Fairness	2018	Sam Corbett‐Davies Sharad Goel	2
+	Towards A Rigorous Science of Interpretable Machine Learning	2017	Finale Doshi‐Velez Been Kim	2
+	Statistical Models for Earthquake Occurrences and Residual Analysis for Point Processes	1988	Yosihiko Ogata	2
+ PDF Chat	Geometric Hawkes Processes with Graph Convolutional Recurrent Neural Networks	2019	Jin Shang Mingxuan Sun	2
+	An Evaluation of the Human-Interpretability of Explanation	2019	Isaac Lage Emily Chen Jeffrey He Menaka Narayanan Been Kim Sam Gershman Finale Doshi‐Velez	2
+ PDF Chat	Modeling the Intensity Function of Point Process Via Recurrent Neural Networks	2017	Shuai Xiao Junchi Yan Xiaokang Yang Hongyuan Zha Stephen M. Chu	2
+	Spectra of some self-exciting and mutually exciting point processes	1971	Alan G. Hawkes	2
+ PDF Chat	Enslaving the Algorithm: From a “Right to an Explanation” to a “Right to Better Decisions”?	2018	Lilian Edwards Michael Veale	2
+	Recurrent Marked Temporal Point Processes	2016	Nan Du Hanjun Dai Rakshit Trivedi Utkarsh Upadhyay Manuel Gomez-Rodriguez Le Song	2
+	FastPoint: Scalable Deep Point Processes	2020	Ali Caner Türkmen Yuyang Wang Alexander J. Smola	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
+	“Why Should I Trust You?”: Explaining the Predictions of Any Classifier	2016	Marco Ribeiro Sameer Singh Carlos Guestrin	2
+	Metrics for Explainable AI: Challenges and Prospects	2018	Robert R. Hoffman Shane T. Mueller Gary Klein Jordan A. Litman	2
+	Manipulating and Measuring Model Interpretability	2018	Forough Poursabzi-Sangdeh Daniel G. Goldstein Jake M. Hofman Jennifer Wortman Vaughan Hanna Wallach	2
+	Explanation in artificial intelligence: Insights from the social sciences	2018	Tim Miller	2
+ PDF Chat	Proxy tasks and subjective measures can be misleading in evaluating explainable AI systems	2020	Zana Buçinca Phoebe Lin Krzysztof Z. Gajos Elena L. Glassman	2
+	To Trust Or Not To Trust A Classifier	2018	Heinrich Jiang Been Kim Melody Y. Guan Maya R. Gupta	1
+	Evidential Deep Learning to Quantify Classification Uncertainty	2018	Murat Şensoy Lance Kaplan Melih Kandemir	1
+	Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks	2019	Guotai Wang Wenqi Li Michaël Aertsen Jan Deprest Sébastien Ourselin Tom Vercauteren	1
+	Metrics for Explainable AI: Challenges and Prospects.	2018	Robert R. Hoffman Shane T. Mueller Gary Klein Jordan A. Litman	1
+	From Variational to Deterministic Autoencoders	2019	Partha Ghosh Mehdi S. M. Sajjadi Antonio Vergari Michael J. Black Bernhard Schölkopf	1
+	Relational Representation Learning for Dynamic (Knowledge) Graphs: A Survey.	2019	Seyed Mehran Kazemi Rishab Goel Kshitij Jain Ivan Kobyzev Akshay Sethi Peter Forsyth Pascal Poupart	1
+	Learning Temporal Point Processes via Reinforcement Learning	2018	Shuang Li Shuai Xiao Shixiang Zhu Nan Du Yao Xie Le Song	1
+	Censoring Representations with an Adversary	2015	Harrison Edwards Amos Storkey	1
+	An Empirical Study of Rich Subgroup Fairness for Machine Learning	2019	Michael Kearns Seth Neel Aaron Roth Zhiwei Steven Wu	1
+	Mitigating Unwanted Biases with Adversarial Learning	2018	Brian Hu Zhang Blake Lemoine Margaret Mitchell	1
+	Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles	2016	Balaji Lakshminarayanan Alexander Pritzel Charles Blundell	1
+	Semi-Supervised Classification with Graph Convolutional Networks	2016	Thomas Kipf Max Welling	1
+	Multivariate Hawkes Processes for Large-scale Inference	2016	Rémi Lemonnier Kevin Scaman Argyris Kalogeratos	1
+	Modeling Event Propagation via Graph Biased Temporal Point Process	2019	Weichang Wu Huanxi Liu Xiaohu Zhang Yu Liu Hongyuan Zha	1
+	Learning Hawkes Processes from a handful of events	2019	Farnood Salehi William Trouleau Matthias Grossglauser Patrick Thiran	1
+	Icebreaker: Element-wise Efficient Information Acquisition with a Bayesian Deep Latent Gaussian Model	2019	Wenbo Gong Sebastian Tschiatschek Sebastian Nowozin Richard E. Turner José Miguel Hernández-Lobato Cheng Zhang	1
+ PDF Chat	Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep Ensembles	2020	Siddhartha Jain Ge Liu Jonas Mueller David K. Gifford	1
+	Try Depth Instead of Weight Correlations: Mean-field is a Less Restrictive Assumption for Deeper Networks.	2020	Sebastian Farquhar Lewis Smith Yarin Gal	1
+ PDF Chat	Uncertainty-Aware Audiovisual Activity Recognition Using Deep Bayesian Variational Inference	2019	Mahesh Subedar Ranganath Krishnan Paulo Lopez Meyer Omesh Tickoo Jonathan Huang	1
+ PDF Chat	Does Explainable Artificial Intelligence Improve Human Decision-Making?	2021	Yasmeen Alufaisan Laura R. Marusich Jonathan Z. Bakdash Yan Zhou Murat Kantarcıoğlu	1
+ PDF Chat	Modeling Event Propagation via Graph Biased Temporal Point Process	2020	Weichang Wu Huanxi Liu Xiaohu Zhang Yu Liu Hongyuan Zha	1
+	A review of uncertainty quantification in deep learning: Techniques, applications and challenges	2021	Moloud Abdar Farhad Pourpanah Sadiq Hussain Dana Rezazadegan Li Liu Mohammad Ghavamzadeh Paul Fieguth Xiaochun Cao Abbas Khosravi U. Rajendra Acharya	1
+ PDF Chat	Enslaving the Algorithm: From a “Right to an Explanation” to a “Right to Better Decisions”?	2018	Lilian Edwards Michael Veale	1
+ PDF Chat	To Explain or to Predict?	2010	Galit Shmueli	1
+	Reactive point processes: A new approach to predicting power failures in underground electrical systems	2015	Şeyda Ertekin Cynthia Rudin Tyler H. McCormick	1
+ PDF Chat	To Trust or to Think	2021	Zana Buçinca Maja Barbara Malaya Krzysztof Z. Gajos	1
+	Astrologer: Exploiting graph neural Hawkes process for event propagation prediction with spatio-temporal characteristics	2021	Haizhou Du Yan Zhou Yunpu Ma Shiwei Wang	1
+	Hawkes process modeling of COVID-19 with mobility leading indicators and spatial covariates	2021	Wen-Hao Chiang Xueying Liu George Mohler	1
+	Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty	2021	Umang Bhatt Javier Antorán Yunfeng Zhang Q. Vera Liao Prasanna Sattigeri Riccardo Fogliato Gabrielle Gauthier Melançon Ranganath Krishnan Jason Stanley Omesh Tickoo	1
+	Neural Relation Inference for Multi-dimensional Temporal Point Processes via Message Passing Graph	2021	Yunhao Zhang Junchi Yan	1