Kyle Vedder

According to our database, Kyle Vedder authored at least 12 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Toward Scalable, Flexible Scene Flow for Point Clouds.

Kyle Vedder

CoRR, March, 2025

Neural Eulerian Scene Flow Fields.

Kyle Vedder, Neehar Peri, Ishan Khatri, Siyi Li, Eric Eaton, Mehmet Kemal Kocamaz, Yue Wang, Zhiding Yu, Deva Ramanan, Joachim Pehserl

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Articulate-Anything: Automatic Modeling of Articulated Objects via a Vision-Language Foundation Model.

Long Le, Jason Xie, William Liang, Hung-Ju Wang, Yue Yang, Yecheng Jason Ma, Kyle Vedder, Arjun Krishna, Dinesh Jayaraman, Eric Eaton

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

A collective AI via lifelong learning and sharing at the edge.

Andrea Soltoggio, Eseoghene Ben-Iwhiwhu, Vladimir Braverman, Eric Eaton, Benjamin Epstein, Yunhao Ge, Lucy Halperin, Jonathan P. How, Laurent Itti, Michael A. Jacobs, Pavan Kantharaju, Long Le, Steven Lee, Xinran Liu, Sildomar T. Monteiro, David Musliner, Saptarshi Nath, Priyadarshini Panda, Christos Peridis, Hamed Pirsiavash, Vishwa S. Parekh, Kaushik Roy, Shahaf S. Shperberg, Hava T. Siegelmann, Peter Stone, Kyle Vedder, Jingfeng Wu, Lin Yang, Guangyao Zheng, Soheil Kolouri

Nat. Mac. Intell., 2024

ZeroFlow: Scalable Scene Flow via Distillation.

Kyle Vedder, Neehar Peri, Nathaniel Chodosh, Ishan Khatri, Eric Eaton, Dinesh Jayaraman, Yang Liu, Deva Ramanan, James Hays

Proceedings of the Twelfth International Conference on Learning Representations, 2024

I Can't Believe It's Not Scene Flow!

Ishan Khatri, Kyle Vedder, Neehar Peri, Deva Ramanan, James Hays

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

A domain-agnostic approach for characterization of lifelong learning systems.

Megan M. Baker, Alexander New, Mario Aguilar-Simon, Ziad Al-Halah, Sébastien M. R. Arnold, Eseoghene Ben-Iwhiwhu, Andrew P. Brna, Ethan Brooks, Ryan C. Brown, Zachary Daniels, Anurag Reddy Daram, Fabien Delattre, Ryan Dellana, Eric Eaton, Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, Cassandra Kent, Nicholas Ketz, Soheil Kolouri, George Konidaris, Dhireesha Kudithipudi, Erik G. Learned-Miller, Seungwon Lee, Michael Littman, Sandeep Madireddy, Jorge A. Mendez, Eric Q. Nguyen, Christine D. Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan, Neale Ratzlaff, Andrea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang, Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel Yedidsion, Shangqun Yu, Gautam K. Vallabha

Neural Networks, March, 2023

ZeroFlow: Fast Zero Label Scene Flow via Distillation.

Kyle Vedder, Neehar Peri, Nathaniel Chodosh, Ishan Khatri, Eric Eaton, Dinesh Jayaraman, Yang Liu, Deva Ramanan, James Hays

CoRR, 2023

2022

Sparse PointPillars: Maintaining and Exploiting Input Sparsity to Improve Runtime on Embedded Systems.

Kyle Vedder, Eric Eaton

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

2021

Sparse PointPillars: Exploiting Sparsity in Birds-Eye-View Object Detection.

Kyle Vedder, Eric Eaton

CoRR, 2021

X*: Anytime Multi-Agent Path Finding for Sparse Domains using Window-Based Iterative Repairs.

Kyle Vedder, Joydeep Biswas

Artif. Intell., 2021

2019

X*: Anytime Multiagent Planning With Bounded Search.

Kyle Vedder, Joydeep Biswas

Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019