Peter Ondrúška
Peter Ondrúška
Head of Research, Lyft Level 5
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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
9392016
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
2262016
Maximum entropy deep inverse reinforcement learning
M Wulfmeier, P Ondruska, I Posner
arXiv preprint arXiv:1507.04888, 2015
1592015
Deep tracking: Seeing beyond seeing using recurrent neural networks
P Ondruska, I Posner
arXiv preprint arXiv:1602.00991, 2016
1342016
Mobilefusion: Real-time volumetric surface reconstruction and dense tracking on mobile phones
P Ondrúška, P Kohli, S Izadi
IEEE transactions on visualization and computer graphics 21 (11), 1251-1258, 2015
962015
Deep tracking: Seeing beyond seeing using recurrent neural networks
P Ondrúška, I Posner
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence …, 2016
692016
Deep tracking in the wild: End-to-end tracking using recurrent neural networks
J Dequaire, P Ondrúška, D Rao, D Wang, I Posner
The International Journal of Robotics Research 37 (4-5), 492-512, 2018
602018
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
532017
Deep inverse reinforcement learning
M Wulfmeier, P Ondruska, I Posner
CoRR, abs/1507.04888, 2015
492015
Lyft level 5 av dataset 2019
R Kesten, M Usman, J Houston, T Pandya, K Nadhamuni, A Ferreira, ...
urlhttps://level5. lyft. com/dataset, 2019
352019
Probabilistic attainability maps: Efficiently predicting driver-specific electric vehicle range
P Ondrúška, I Posner
2014 IEEE Intelligent Vehicles Symposium Proceedings, 1169-1174, 2014
272014
The route not taken: Driver-centric estimation of electric vehicle range
P Ondrúška, I Posner
Proceedings of the Twenty-Fourth International Conferenc on International …, 2014
252014
Scheduled perception for energy-efficient path following
P Ondrúška, C Gurău, L Marchegiani, CH Tong, I Posner
2015 IEEE International Conference on Robotics and Automation (ICRA), 4799-4806, 2015
232015
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
192016
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
162019
One Thousand and One Hours: Self-driving Motion Prediction Dataset
J Houston, G Zuidhof, L Bergamini, Y Ye, A Jain, S Omari, V Iglovikov, ...
arXiv preprint arXiv:2006.14480, 2020
12020
Visual vehicle tracking through noise and occlusions using crowd-sourced maps
MS Suraj, H Grimmett, L Platinský, P Onduska
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018
12018
VALUE: Large Scale Voting-based Automatic Labelling for Urban Environments
G Dabisias, E Ruffaldi, H Grimmett, P Ondruska
2018 IEEE International Conference on Robotics and Automation (ICRA), 1-6, 2018
12018
Urban environment labelling
P Ondruska, L Platinsky, G Dabisias
US Patent 10,706,576, 2020
2020
Vehicle tracking
P Ondruska, L Platinsky, SM Surendran
US Patent 10,696,300, 2020
2020
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Artículos 1–20