David S. Hayden

18 papers A* 5A 4Journal 7Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Causal Composition Diffusion Model for Closed-loop Traffic Generation. CVPR Haohong Lin, Xin Huang, Tung Phan, David S. Hayden, Huan Zhang, Ding Zhao, Siddhartha S. Srinivasa, Eric M. Wolff, Hongge Chen
2025	A*	`conf`	DriveGPT: Scaling Autoregressive Behavior Models for Driving. ICML 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, Pratik Agarwal, Tianshi Gao, Yuning Chai, Siddhartha S. Srinivasa
2025	A*	`conf`	Generative Data Mining with Longtail-Guided Diffusion. ICML David S. Hayden, Mao Ye, Timur Garipov, Gregory P. Meyer, Carl Vondrick, Zhao Chen, Yuning Chai, Eric M. Wolff, Siddhartha S. Srinivasa
2025	J	`jnl`	Generative Data Mining with Longtail-Guided Diffusion. CoRR David S. Hayden, Mao Ye, Timur Garipov, Gregory P. Meyer, Carl Vondrick, Zhao Chen, Yuning Chai, Eric M. Wolff, Siddhartha S. Srinivasa
2024	J	`jnl`	Causal Composition Diffusion Model for Closed-loop Traffic Generation. CoRR Haohong Lin, Xin Huang, Tung Phan-Minh, David S. Hayden, Huan Zhang, Ding Zhao, Siddhartha S. Srinivasa, Eric M. Wolff, Hongge Chen
2024	J	`jnl`	DriveGPT: Scaling Autoregressive Behavior Models for Driving. CoRR 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, Pratik Agarwal, Tianshi Gao, Yuning Chai, Siddhartha S. Srinivasa
2021	—	`—`	Uncertainty Quantification and Structure Discovery for Scalable Behavior Science. David S. Hayden
2020	J	`jnl`	Efficient Data Association and Uncertainty Quantification for Multi-Object Tracking. CoRR David S. Hayden, Sue Zheng, John W. Fisher III
2020	A*	`conf`	Nonparametric Object and Parts Modeling With Lie Group Dynamics. CVPR David S. Hayden, Jason Pacheco, John W. Fisher III
2020	A*	`conf`	Sequential Bayesian Experimental Design with Variable Cost Structure. NeurIPS Sue Zheng, David S. Hayden, Jason Pacheco, John W. Fisher III
2012	J	`jnl`	Using Clustering and Metric Learning to Improve Science Return of Remote Sensed Imagery. ACM Trans. Intell. Syst. Technol. David S. Hayden, Steve A. Chien, David R. Thompson, Rebecca Castaño
2011	A	`conf`	Note-taker 3.0: an assistive technology enabling students who are legally blind to take notes in class. ASSETS David S. Hayden, Michael J. Astrauskas, Qian Yan, Liqing Zhou, John A. Black Jr.
2011	J	`jnl`	Student project aimed at helping the visually impaired take notes in class wins prize at Microsoft Imagine Cup. ACM SIGACCESS Access. Comput. Michael J. Astrauskas, David S. Hayden, Qian Yan, John A. Black Jr.
2010	A	`conf`	Note-taker 2.0: the next step toward enabling students who are legally blind to take notes in class. ASSETS David S. Hayden, Liqing Zhou, Michael J. Astrauskas, John A. Black Jr.
2010	—	`conf`	The Note-Taker: An assistive technology that allows students who are legally blind to take notes in the classroom. CVPR Workshops John A. Black Jr., David S. Hayden
2010	J	`jnl`	Using Onboard Clustering to Summarize Remotely Sensed Imagery. IEEE Intell. Syst. David S. Hayden, Steve A. Chien, David R. Thompson, Rebecca Castaño
2008	A	`conf`	Enabling the legally blind in classroom note-taking. ASSETS David S. Hayden, Dirk Colbry, John A. Black Jr., Sethuraman Panchanathan
2008	A	`conf`	Note-taker: enabling students who are legally blind to take notes in class. ASSETS David S. Hayden, Dirk Colbry, John A. Black Jr., Sethuraman Panchanathan