Note-taker: enabling students who are legally blind to take notes in class. - David S. Hayden; Dirk Colbry; John A. Black Jr.; Sethuraman Panchanathan (ASSETS, 2008)

Enabling the legally blind in classroom note-taking. - David S. Hayden; Dirk Colbry; John A. Black Jr.; Sethuraman Panchanathan (ASSETS, 2008)

Note-taker 2.0: the next step toward enabling students who are legally blind to take notes in class. - David S. Hayden; Liqing Zhou; Michael J. Astrauskas; John A. Black Jr. (ASSETS, 2010)

The Note-Taker: An assistive technology that allows students who are legally blind to take notes in the classroom. - John A. Black Jr.; David S. Hayden (CVPR Workshops, 2010)

Using Onboard Clustering to Summarize Remotely Sensed Imagery. - David S. Hayden; Steve A. Chien; David R. Thompson 001; Rebecca Castaño (IEEE Intell. Syst., 2010)

Note-taker 3.0: an assistive technology enabling students who are legally blind to take notes in class. - David S. Hayden; Michael J. Astrauskas; Qian Yan; Liqing Zhou; John A. Black Jr. (ASSETS, 2011)

Student project aimed at helping the visually impaired take notes in class wins prize at Microsoft Imagine Cup. - Michael J. Astrauskas; David S. Hayden; Qian Yan; John A. Black Jr. (ACM SIGACCESS Access. Comput., 2011)

Using Clustering and Metric Learning to Improve Science Return of Remote Sensed Imagery. - David S. Hayden; Steve A. Chien; David R. Thompson 001; Rebecca Castaño (ACM Trans. Intell. Syst. Technol., 2012)

Nonparametric Object and Parts Modeling With Lie Group Dynamics. - David S. Hayden; Jason Pacheco; John W. Fisher III (CVPR, 2020)

Sequential Bayesian Experimental Design with Variable Cost Structure. - Sue Zheng; David S. Hayden; Jason Pacheco; John W. Fisher III (NeurIPS, 2020)

Efficient Data Association and Uncertainty Quantification for Multi-Object Tracking. - David S. Hayden; Sue Zheng; John W. Fisher III (CoRR, 2020)

Uncertainty Quantification and Structure Discovery for Scalable Behavior Science. - David S. Hayden (2021)

DriveGPT: Scaling Autoregressive Behavior Models for Driving. - Xin Huang; Eric M. Wolff; Paul Vernaza; Tung Phan-Minh; Hongge Chen; David S. Hayden; Mark Edmonds; Brian Pierce; Xinxin Chen; Pratik Elias Jacob; Xiaobai Chen; Chingiz Tairbekov; et al. (CoRR, 2024)

Causal Composition Diffusion Model for Closed-loop Traffic Generation. - Haohong Lin; Xin Huang; Tung Phan-Minh; David S. Hayden; Huan Zhang 001; Ding Zhao; Siddhartha S. Srinivasa; Eric M. Wolff; Hongge Chen (CoRR, 2024)

Causal Composition Diffusion Model for Closed-loop Traffic Generation. - Haohong Lin; Xin Huang; Tung Phan; David S. Hayden; Huan Zhang 001; Ding Zhao; Siddhartha S. Srinivasa; Eric M. Wolff; Hongge Chen (CVPR, 2025)

Generative Data Mining with Longtail-Guided Diffusion. - David S. Hayden; Mao Ye 006; Timur Garipov; Gregory P. Meyer; Carl Vondrick; Zhao Chen; Yuning Chai; Eric M. Wolff; Siddhartha S. Srinivasa (CoRR, 2025)