Peter Ondruska

Publication Activity (10 Years)

Years Active: 2014-2022
Publications (10 Years): 29

Top Topics

Language Processing

Recurrent Neural Networks

Augmented Reality

Reinforcement Learning

Top Venues

Intelligent Vehicles Symposium

Int. J. Robotics Res.

Publications

Matt Vitelli, Yan Chang, Yawei Ye, Ana Ferreira, Maciej Wolczyk, Blazej Osinski, Moritz Niendorf, Hugo Grimmett, Qiangui Huang, Ashesh Jain, Peter Ondruska
SafetyNet: Safe Planning for Real-World Self-Driving Vehicles Using Machine-Learned Policies. ICRA (2022)
Oliver Scheel, Luca Bergamini, Maciej Wolczyk, Blazej Osinski, Peter Ondruska
Urban Driver: Learning to Drive from Real-world Demonstrations Using Policy Gradients. CoRR (2021)
Long Chen, Lukas Platinsky, Stefanie Speichert, Blazej Osinski, Oliver Scheel, Yawei Ye, Hugo Grimmett, Luca Del Pero, Peter Ondruska
What data do we need for training an AV motion planner? CoRR (2021)
Ashesh Jain, Luca Del Pero, Hugo Grimmett, Peter Ondruska
Autonomy 2.0: Why is self-driving always 5 years away? CoRR (2021)
Long Chen, Lukas Platinsky, Stefanie Speichert, Blazej Osinski, Oliver Scheel, Yawei Ye, Hugo Grimmett, Luca Del Pero, Peter Ondruska
What data do we need for training an AV motion planner? ICRA (2021)
Parth Kothari, Christian Perone, Luca Bergamini, Alexandre Alahi, Peter Ondruska
DriverGym: Democratising Reinforcement Learning for Autonomous Driving. CoRR (2021)
Luca Bergamini, Yawei Ye, Oliver Scheel, Long Chen, Chih Hu, Luca Del Pero, Blazej Osinski, Hugo Grimmett, Peter Ondruska
SimNet: Learning Reactive Self-driving Simulations from Real-world Observations. CoRR (2021)
Matt Vitelli, Yan Chang, Yawei Ye, Maciej Wolczyk, Blazej Osinski, Moritz Niendorf, Hugo Grimmett, Qiangui Huang, Ashesh Jain, Peter Ondruska
SafetyNet: Safe planning for real-world self-driving vehicles using machine-learned policies. CoRR (2021)
Luca Bergamini, Yawei Ye, Oliver Scheel, Long Chen, Chih Hu, Luca Del Pero, Blazej Osinski, Hugo Grimmett, Peter Ondruska
SimNet: Learning Reactive Self-driving Simulations from Real-world Observations. ICRA (2021)
Oliver Scheel, Luca Bergamini, Maciej Wolczyk, Blazej Osinski, Peter Ondruska
Urban Driver: Learning to Drive from Real-world Demonstrations Using Policy Gradients. CoRL (2021)
Lukas Platinsky, Michal Szabados, Filip Hlasek, Ross Hemsley, Luca Del Pero, Andrej Pancik, Bryan Baum, Hugo Grimmett, Peter Ondruska
Collaborative Augmented Reality on Smartphones via Life-long City-scale Maps. CoRR (2020)
John Houston, Guido Zuidhof, Luca Bergamini, Yawei Ye, Ashesh Jain, Sammy Omari, Vladimir Iglovikov, Peter Ondruska
One Thousand and One Hours: Self-driving Motion Prediction Dataset. CoRR (2020)
John Houston, Guido Zuidhof, Luca Bergamini, Yawei Ye, Long Chen, Ashesh Jain, Sammy Omari, Vladimir Iglovikov, Peter Ondruska
One Thousand and One Hours: Self-driving Motion Prediction Dataset. CoRL (2020)
Lukas Platinsky, Michal Szabados, Filip Hlasek, Ross Hemsley, Luca Del Pero, Andrej Pancik, Bryan Baum, Hugo Grimmett, Peter Ondruska
Collaborative Augmented Reality on Smartphones via Life-long City-scale Maps. ISMAR (2020)
Giacomo Dabisias, Emanuele Ruffaldi, Hugo Grimmett, Peter Ondruska
VALUE: Large Scale Voting-based Automatic Labelling for Urban Environments. CoRR (2020)
Julie Dequaire, Peter Ondruska, Dushyant Rao, Dominic Zeng Wang, Ingmar Posner
Deep tracking in the wild: End-to-end tracking using recurrent neural networks. Int. J. Robotics Res. 37 (4-5) (2018)
M. S. Suraj, Hugo Grimmett, Lukas Platinsky, Peter Ondruska
Visual Vehicle Tracking Through Noise and Occlusions Using Crowd-Sourced Maps. IROS (2018)
M. S. Suraj, Hugo Grimmett, Lukas Platinsky, Peter Ondruska
Predicting trajectories of vehicles using large-scale motion priors. Intelligent Vehicles Symposium (2018)
Giacomo Dabisias, Emanuele Ruffaldi, Hugo Grimmett, Peter Ondruska
VALUE: Large Scale Voting-Based Automatic Labelling for Urban Environments. ICRA (2018)
Markus Wulfmeier, Dushyant Rao, Dominic Zeng Wang, Peter Ondruska, Ingmar Posner
Large-scale cost function learning for path planning using deep inverse reinforcement learning. Int. J. Robotics Res. 36 (10) (2017)
Ankit Kumar, Ozan Irsoy, Peter Ondruska, Mohit Iyyer, James Bradbury, Ishaan Gulrajani, Victor Zhong, Romain Paulus, Richard Socher
Ask Me Anything: Dynamic Memory Networks for Natural Language Processing. ICML (2016)
Julie Dequaire, Dushyant Rao, Peter Ondruska, Dominic Zeng Wang, Ingmar Posner
Deep Tracking on the Move: Learning to Track the World from a Moving Vehicle using Recurrent Neural Networks. CoRR (2016)
Peter Ondruska, Ingmar Posner
Deep Tracking: Seeing Beyond Seeing Using Recurrent Neural Networks. CoRR (2016)
Peter Ondruska, Ingmar Posner
Deep Tracking: Seeing Beyond Seeing Using Recurrent Neural Networks. AAAI (2016)
Peter Ondruska, Julie Dequaire, Dominic Zeng Wang, Ingmar Posner
End-to-End Tracking and Semantic Segmentation Using Recurrent Neural Networks. CoRR (2016)
Peter Ondruska, Corina Gurau, Letizia Marchegiani, Chi Hay Tong, Ingmar Posner
Scheduled perception for energy-efficient path following. ICRA (2015)
Markus Wulfmeier, Peter Ondruska, Ingmar Posner
Deep Inverse Reinforcement Learning. CoRR (2015)
Ankit Kumar, Ozan Irsoy, Jonathan Su, James Bradbury, Robert English, Brian Pierce, Peter Ondruska, Ishaan Gulrajani, Richard Socher
Ask Me Anything: Dynamic Memory Networks for Natural Language Processing. CoRR (2015)
Peter Ondruska, Pushmeet Kohli, Shahram Izadi
MobileFusion: Real-Time Volumetric Surface Reconstruction and Dense Tracking on Mobile Phones. IEEE Trans. Vis. Comput. Graph. 21 (11) (2015)
Peter Ondruska, Ingmar Posner
Probabilistic attainability maps: Efficiently predicting driver-specific electric vehicle range. Intelligent Vehicles Symposium (2014)
Peter Ondruska, Ingmar Posner
The Route Not Taken: Driver-Centric Estimation of Electric Vehicle Range. ICAPS (2014)