Paul Vernaza

35 papers A* 15A 3B 1Journal 9Unranked 7
YearRankTypeTitle / Venue / Authors
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
Flash3D: Super-scaling Point Transformers through Joint Hardware-Geometry Locality.
CVPR
Liyan Chen, Gregory P. Meyer, Zaiwei Zhang, Eric M. Wolff, Paul Vernaza
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
2024 J jnl
Flash3D: Super-scaling Point Transformers through Joint Hardware-Geometry Locality.
CoRR
Liyan Chen, Gregory P. Meyer, Zaiwei Zhang, Eric M. Wolff, Paul Vernaza
2022 A* conf
Towards Uniformly Superhuman Autonomy via Subdominance Minimization.
ICML
Brian D. Ziebart, Sanjiban Choudhury, Xinyan Yan, Paul Vernaza
2018 — conf
Hierarchical Metric Learning and Matching for 2D and 3D Geometric Correspondences.
ECCV (15)
Mohammed E. Fathy, Quoc-Huy Tran, M. Zeeshan Zia, Paul Vernaza, Manmohan Chandraker
2018 J jnl
Hierarchical Metric Learning and Matching for 2D and 3D Geometric Correspondences.
CoRR
Mohammed E. Fathy, Quoc-Huy Tran, M. Zeeshan Zia, Paul Vernaza, Manmohan Chandraker
2018 J jnl
Learning random-walk label propagation for weakly-supervised semantic segmentation.
CoRR
Paul Vernaza, Manmohan Chandraker
2018 — conf
r2p2: A ReparameteRized Pushforward Policy for Diverse, Precise Generative Path Forecasting.
ECCV (13)
Nicholas Rhinehart, Kris M. Kitani, Paul Vernaza
2017 A* conf
DESIRE: Distant Future Prediction in Dynamic Scenes with Interacting Agents.
CVPR
Namhoon Lee, Wongun Choi, Paul Vernaza, Christopher B. Choy, Philip H. S. Torr, Manmohan Chandraker
2017 J jnl
DESIRE: Distant Future Prediction in Dynamic Scenes with Interacting Agents.
CoRR
Namhoon Lee, Wongun Choi, Paul Vernaza, Christopher B. Choy, Philip H. S. Torr, Manmohan Krishna Chandraker
2017 J jnl
Deep Network Flow for Multi-Object Tracking.
CoRR
Samuel Schulter, Paul Vernaza, Wongun Choi, Manmohan Chandraker
2017 A* conf
Deep Network Flow for Multi-object Tracking.
CVPR
Samuel Schulter, Paul Vernaza, Wongun Choi, Manmohan Chandraker
2017 A* conf
Learning Random-Walk Label Propagation for Weakly-Supervised Semantic Segmentation.
CVPR
Paul Vernaza, Manmohan Chandraker
2016 J jnl
Variational reaction-diffusion systems for semantic segmentation.
CoRR
Paul Vernaza
2015 A conf
Learning product set models of fault triggers in high-dimensional software interfaces.
IROS
Paul Vernaza, David Guttendorf, Michael Wagner, Philip Koopman
2014 — conf
Learning to locate from demonstrated searches.
Robotics: Science and Systems
Paul Vernaza, Anthony Stentz
2013 A* conf
Continuous planning with winding constraints using optimal heuristic-driven front propagation.
ICRA
Dmitry S. Yershov, Paul Vernaza, Steven M. LaValle
2013 A* conf
Planning under topological constraints using beam-graphs.
ICRA
Venkatraman Narayanan, Paul Vernaza, Maxim Likhachev, Steven M. LaValle
2012 — conf
Efficient high dimensional maximum entropy modeling via symmetric partition functions.
NIPS
Paul Vernaza, Drew Bagnell
2012 B conf
Efficiently Finding Optimal Winding-Constrained Loops in the Plane: Extended Abstract.
SOCS
Paul Vernaza, Venkatraman Narayanan, Maxim Likhachev
2012 — conf
Efficiently finding optimal winding-constrained loops in the plane.
Robotics: Science and Systems
Paul Vernaza, Venkatraman Narayanan, Maxim Likhachev
2012 J jnl
Learning and exploiting low-dimensional structure for efficient holonomic motion planning in high-dimensional spaces.
Int. J. Robotics Res.
Paul Vernaza, Daniel D. Lee
2011 A* conf
Efficient dynamic programming for high-dimensional, optimal motion planning by spectral learning of approximate value function symmetries.
ICRA
Paul Vernaza, Daniel D. Lee
2011 A* conf
Learning Dimensional Descent for Optimal Motion Planning in High-dimensional Spaces.
AAAI
Paul Vernaza, Daniel D. Lee
2011 A conf
Learning Dimensional Descent planning for a highly-articulated robot arm.
IROS
Paul Vernaza, Daniel D. Lee
2010 A* conf
Learning and planning high-dimensional physical trajectories via structured Lagrangians.
ICRA
Paul Vernaza, Daniel D. Lee, Seung-Joon Yi
2010 A* conf
Scalable real-time object recognition and segmentation via cascaded, discriminative Markov random fields.
ICRA
Paul Vernaza, Daniel D. Lee
2009 — conf
Little Ben: The Ben Franklin Racing Team's Entry in the 2007 DARPA Urban Challenge.
The DARPA Urban Challenge
Jonathan Bohren, Tully Foote, Jim Keller, Alex Kushleyev, Daniel D. Lee, Alex Stewart, Paul Vernaza, Jason C. Derenick, John R. Spletzer, Brian Satterfield
2009 A* conf
Search-based planning for a legged robot over rough terrain.
ICRA
Paul Vernaza, Maxim Likhachev, Subhrajit Bhattacharya, Sachin Chitta, Aleksandr Kushleyev, Daniel D. Lee
2008 J jnl
Little Ben: The Ben Franklin Racing Team's entry in the 2007 DARPA Urban Challenge.
J. Field Robotics
Jonathan Bohren, Tully Foote, Jim Keller, Alex Kushleyev, Daniel D. Lee, Alex Stewart, Paul Vernaza, Jason C. Derenick, John R. Spletzer, Brian Satterfield
2008 A* conf
Online, self-supervised terrain classification via discriminatively trained submodular Markov random fields.
ICRA
Paul Vernaza, Ben Taskar, Daniel D. Lee
2006 A* conf
Rao-Blackwellized Particle Filtering for 6-DOF Estimation of Attitude and Position via GPS and Inertial Sensors.
ICRA
Paul Vernaza, Daniel D. Lee
2006 — conf
Robust GPS/INS-Aided Localization and Mapping Via GPS Bias Estimation.
ISER
Paul Vernaza, Daniel D. Lee
2005 A conf
Cooperative relative robot localization with audible acoustic sensing.
IROS
Yuanqing Lin, Paul Vernaza, Jihun Ham, Daniel D. Lee