Vernaza, Paul

10 publications

ICML 2025 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 Srinivasa

CVPR 2025 Flash3D: Super-Scaling Point Transformers Through Joint Hardware-Geometry Locality Liyan Chen, Gregory P. Meyer, Zaiwei Zhang, Eric M. Wolff, Paul Vernaza

ICML 2022 Towards Uniformly Superhuman Autonomy via Subdominance Minimization Brian Ziebart, Sanjiban Choudhury, Xinyan Yan, Paul Vernaza

ECCV 2018 Hierarchical Metric Learning and Matching for 2D and 3D Geometric Correspondences Mohammed E. Fathy, Quoc-Huy Tran, M. Zeeshan Zia, Paul Vernaza, Manmohan Chandraker

ECCV 2018 R2P2: A ReparameteRized Pushforward Policy for Diverse, Precise Generative Path Forecasting Nicholas Rhinehart, Kris M. Kitani, Paul Vernaza

CVPR 2017 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

CVPR 2017 Deep Network Flow for Multi-Object Tracking Samuel Schulter, Paul Vernaza, Wongun Choi, Manmohan Chandraker

CVPR 2017 Learning Random-Walk Label Propagation for Weakly-Supervised Semantic Segmentation Paul Vernaza, Manmohan Chandraker

NeurIPS 2012 Efficient High Dimensional Maximum Entropy Modeling via Symmetric Partition Functions Paul Vernaza, Drew Bagnell

AAAI 2011 Learning Dimensional Descent for Optimal Motion Planning in High-Dimensional Spaces Paul Vernaza, Daniel D. Lee