Peter Ondrúška
Peter Ondrúška
Lyft Level 5
Verified email at ondruska.com - Homepage
TitleCited byYear
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
5772016
Deep tracking: Seeing beyond seeing using recurrent neural networks
P Ondruska, I Posner
Thirtieth AAAI Conference on Artificial Intelligence, 2016
1222016
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
772015
Maximum entropy deep inverse reinforcement learning
M Wulfmeier, P Ondruska, I Posner
arXiv preprint arXiv:1507.04888, 2015
772015
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
342016
Deep inverse reinforcement learning
M Wulfmeier, P Ondruska, I Posner
arXiv preprint arXiv:1507.04888, 2015
312015
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
272018
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
202015
Probabilistic attainability maps: Efficiently predicting driver-specific electric vehicle range
P Ondrúška, I Posner
2014 IEEE Intelligent Vehicles Symposium Proceedings, 1169-1174, 2014
202014
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
192014
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
152017
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
92016
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
Neural Robotics-A New Perspective AAAI Robotics Fellowship 2016
P Ondruska
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