Peter Ondr˙ška
Peter Ondr˙ška
Head of Research, Lyft Level 5
Verified email at ondruska.com - Homepage
Title
Cited by
Cited by
Year
Ask me anything: Dynamic memory networks for natural language processing
A Kumar, O Irsoy, P Ondruska, M Iyyer, J Bradbury, I Gulrajani, V Zhong, ...
International conference on machine learning, 1378-1387, 2016
11012016
Maximum entropy deep inverse reinforcement learning
M Wulfmeier, P Ondruska, I Posner
arXiv preprint arXiv:1507.04888, 2015
2152015
Deep tracking: Seeing beyond seeing using recurrent neural networks
P Ondruska, I Posner
Thirtieth AAAI conference on artificial intelligence, 2016
1452016
Mobilefusion: Real-time volumetric surface reconstruction and dense tracking on mobile phones
P Ondr˙ška, P Kohli, S Izadi
IEEE transactions on visualization and computer graphics 21 (11), 1251-1258, 2015
1112015
Large-scale cost function learning for path planning using deep inverse reinforcement learning
M Wulfmeier, D Rao, DZ Wang, P Ondruska, I Posner
The International Journal of Robotics Research 36 (10), 1073-1087, 2017
832017
Deep tracking: Seeing beyond seeing using recurrent neural networks
P Ondr˙ška, I Posner
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligenceá…, 2016
752016
Deep tracking in the wild: End-to-end tracking using recurrent neural networks
J Dequaire, P Ondr˙ška, D Rao, D Wang, I Posner
The International Journal of Robotics Research 37 (4-5), 492-512, 2018
732018
Lyft level 5 av dataset 2019
R Kesten, M Usman, J Houston, T Pandya, K Nadhamuni, A Ferreira, ...
urlhttps://level5. lyft. com/dataset, 2019
612019
End-to-end tracking and semantic segmentation using recurrent neural networks
P Ondruska, J Dequaire, DZ Wang, I Posner
arXiv preprint arXiv:1604.05091, 2016
592016
Deep inverse reinforcement learning
M Wulfmeier, P Ondruska, I Posner
CoRR, abs/1507.04888, 2015
552015
One thousand and one hours: Self-driving motion prediction dataset
J Houston, G Zuidhof, L Bergamini, Y Ye, L Chen, A Jain, S Omari, ...
arXiv preprint arXiv:2006.14480, 2020
342020
Probabilistic attainability maps: Efficiently predicting driver-specific electric vehicle range
P Ondruska, I Posner
2014 IEEE Intelligent Vehicles Symposium Proceedings, 1169-1174, 2014
312014
Scheduled perception for energy-efficient path following
P Ondr˙ška, C Gurău, L Marchegiani, CH Tong, I Posner
2015 IEEE International Conference on Robotics and Automation (ICRA), 4799-4806, 2015
292015
Lyft level 5 av dataset 2019. urlhttps
R Kesten, M Usman, J Houston, T Pandya, K Nadhamuni, A Ferreira, ...
level5. lyft. com/dataset 2, 5, 2019
262019
The route not taken: Driver-centric estimation of electric vehicle range
P Ondruska, I Posner
Twenty-Fourth International Conference on Automated Planning and Scheduling, 2014
252014
Deep tracking on the move: Learning to track the world from a moving vehicle using recurrent neural networks
J Dequaire, D Rao, P Ondruska, D Wang, I Posner
arXiv preprint arXiv:1609.09365, 2016
202016
Lyft level 5 perception dataset 2020
R Kesten, M Usman, J Houston, T Pandya, K Nadhamuni, A Ferreira, ...
182019
Collaborative Augmented Reality on Smartphones via Life-long City-scale Maps
L Platinsky, M Szabados, F Hlasek, R Hemsley, L Del Pero, A Pancik, ...
2020 IEEE International Symposium on Mixed and Augmented Reality (ISMARá…, 2020
32020
Method and system for creating a virtual 3D model
P Ondruska, L Platinsky
US Patent 10,460,511, 2019
22019
Visual vehicle tracking through noise and occlusions using crowd-sourced maps
MS Suraj, H Grimmett, L Platinskř, P Ondr˙ška
2018 IEEE/RSJ International Conference on Intelligent Robots and Systemsá…, 2018
12018
The system can't perform the operation now. Try again later.
Articles 1–20