| 2025 | CVPR | Flash3D: Super-scaling Point Transformers through Joint Hardware-Geometry Locality. | Liyan Chen, Gregory P. Meyer, Zaiwei Zhang, Eric M. Wolff, Paul Vernaza |
| 2025 | ICML | 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, Pratik Agarwal, Tianshi Gao, Yuning Chai, Siddhartha S. Srinivasa |
| 2022 | ICML | Towards Uniformly Superhuman Autonomy via Subdominance Minimization. | Brian D. Ziebart, Sanjiban Choudhury, Xinyan Yan, Paul Vernaza |
| 2018 | ECCV | Hierarchical Metric Learning and Matching for 2D and 3D Geometric Correspondences. | Mohammed E. Fathy, Quoc-Huy Tran, M. Zeeshan Zia, Paul Vernaza, Manmohan Chandraker |
| 2018 | ECCV | r2p2: A ReparameteRized Pushforward Policy for Diverse, Precise Generative Path Forecasting. | Nicholas Rhinehart, Kris M. Kitani, Paul Vernaza |
| 2017 | CVPR | DESIRE: Distant Future Prediction in Dynamic Scenes with Interacting Agents. | Namhoon Lee, Wongun Choi, Paul Vernaza, Christopher B. Choy, Philip H. S. Torr, Manmohan Chandraker |
| 2017 | CVPR | Deep Network Flow for Multi-object Tracking. | Samuel Schulter, Paul Vernaza, Wongun Choi, Manmohan Chandraker |
| 2017 | CVPR | Learning Random-Walk Label Propagation for Weakly-Supervised Semantic Segmentation. | Paul Vernaza, Manmohan Chandraker |
| 2015 | IROS | Learning product set models of fault triggers in high-dimensional software interfaces. | Paul Vernaza, David Guttendorf, Michael Wagner, Philip Koopman |
| 2013 | ICRA | Planning under topological constraints using beam-graphs. | Venkatraman Narayanan, Paul Vernaza, Maxim Likhachev, Steven M. LaValle |
| 2013 | ICRA | Continuous planning with winding constraints using optimal heuristic-driven front propagation. | Dmitry S. Yershov, Paul Vernaza, Steven M. LaValle |
| 2012 | SoCS | Efficiently Finding Optimal Winding-Constrained Loops in the Plane: Extended Abstract. | Paul Vernaza, Venkatraman Narayanan, Maxim Likhachev |
| 2011 | AAAI | Learning Dimensional Descent for Optimal Motion Planning in High-dimensional Spaces. | Paul Vernaza, Daniel D. Lee |
| 2011 | IROS | Learning Dimensional Descent planning for a highly-articulated robot arm. | Paul Vernaza, Daniel D. Lee |
| 2011 | ICRA | Efficient dynamic programming for high-dimensional, optimal motion planning by spectral learning of approximate value function symmetries. | Paul Vernaza, Daniel D. Lee |
| 2010 | ICRA | Scalable real-time object recognition and segmentation via cascaded, discriminative Markov random fields. | Paul Vernaza, Daniel D. Lee |
| 2010 | ICRA | Learning and planning high-dimensional physical trajectories via structured Lagrangians. | Paul Vernaza, Daniel D. Lee, Seung-Joon Yi |
| 2009 | ICRA | Search-based planning for a legged robot over rough terrain. | Paul Vernaza, Maxim Likhachev, Subhrajit Bhattacharya, Sachin Chitta, Aleksandr Kushleyev, Daniel D. Lee |
| 2008 | ICRA | Online, self-supervised terrain classification via discriminatively trained submodular Markov random fields. | Paul Vernaza, Ben Taskar, Daniel D. Lee |
| 2006 | ICRA | Rao-Blackwellized Particle Filtering for 6-DOF Estimation of Attitude and Position via GPS and Inertial Sensors. | Paul Vernaza, Daniel D. Lee |
| 2005 | IROS | Cooperative relative robot localization with audible acoustic sensing. | Yuanqing Lin, Paul Vernaza, Jihun Ham, Daniel D. Lee |