Phil Barber

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All published works

Action	Title	Year	Authors
+ PDF Chat	A Survey of Deep Learning Applications to Autonomous Vehicle Control	2020	Sampo Kuutti Richard Bowden Yaochu Jin Phil Barber Saber Fallah
+	A Survey of Deep Learning Applications to Autonomous Vehicle Control	2019	Sampo Kuutti Richard Bowden Yaochu Jin Phil Barber Saber Fallah
+	A Survey of Deep Learning Applications to Autonomous Vehicle Control	2019	Sampo Kuutti Richard Bowden Yaochu Jin Phil Barber Saber Fallah

Common Coauthors

Coauthor	Papers Together
Sampo Kuutti	3
Yaochu Jin	3
Richard Bowden	3
Saber Fallah	3

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	High-Dimensional Continuous Control Using Generalized Advantage Estimation	2015	John Schulman Philipp Moritz Sergey Levine Michael I. Jordan Pieter Abbeel	2
+	Continuous Inverse Optimal Control with Locally Optimal Examples	2012	Sergey Levine Vladlen Koltun	2
+ PDF Chat	Practical Recommendations for Gradient-Based Training of Deep Architectures	2012	Yoshua Bengio	2
+	Improving neural networks by preventing co-adaptation of feature detectors	2012	Geoffrey E. Hinton Nitish Srivastava Alex Krizhevsky Ilya Sutskever Ruslan Salakhutdinov	2
+	Combining Deep Reinforcement Learning and Safety Based Control for Autonomous Driving	2016	Xi Xiong Jianqiang Wang Fang Zhang Keqiang Li	2
+	End-to-End Deep Reinforcement Learning for Lane Keeping Assist	2016	Ahmad El Sallab Mohammed Abdou Etienne Pérot Senthil Yogamani	2
+	Deep Reinforcement Learning: An Overview	2017	Yuxi Li	2
+	CAAD: Computer Architecture for Autonomous Driving	2017	Shaoshan Liu Jie Tang Zhe Zhang Jean‐Luc Gaudiot	2
+	Evolution Strategies as a Scalable Alternative to Reinforcement Learning	2017	Tim Salimans Jonathan Ho Xi Chen Ilya Sutskever	2
+ PDF Chat	Combining neural networks and tree search for task and motion planning in challenging environments	2017	Chris Paxton Vasumathi Raman Gregory D. Hager Marin Kobilarov	2
+ PDF Chat	Feature analysis and selection for training an end-to-end autonomous vehicle controller using deep learning approach	2017	Shun Yang Wenshuo Wang Chang Liu Weiwen Deng J. Karl Hedrick	2
+ PDF Chat	Domain randomization for transferring deep neural networks from simulation to the real world	2017	Josh Tobin Rachel Fong Alex Ray Jonas Schneider Wojciech Zaremba Pieter Abbeel	2
+ PDF Chat	LIDAR-based driving path generation using fully convolutional neural networks	2017	Luca Caltagirone Mauro Bellone Lennart Svensson Mattias Wahde	2
+	Virtual to Real Reinforcement Learning for Autonomous Driving	2017	Xinlei Pan Yurong You Ziyan Wang Cewu Lu	2
+	Learning from Demonstrations for Real World Reinforcement Learning	2017	Todd Hester Matej Vecerík Olivier Pietquin Marc Lanctot Tom Schaul Bilal Piot Andrew Sendonaris Gabriel Dulac-Arnold Ian Osband John Agapiou	2
+	Hybrid reward architecture for reinforcement learning	2017	Harm van Seijen Mehdi Fatemi Joshua Romoff Romain Laroche Tavian Barnes Jeffrey Tsang	2
+	An Analysis of ISO 26262: Using Machine Learning Safely in Automotive Software	2017	Rick Salay Rodrigo Queiroz Krzysztof Czarnecki	2
+	End-to-End Deep Learning for Steering Autonomous Vehicles Considering Temporal Dependencies	2017	Hesham M. Eraqi Mohamed Moustafa Jens Honer	2
+	Parallel Architecture and Hyperparameter Search via Successive Halving and Classification.	2018	Manoj Kumar George E. Dahl Vijay Vasudevan Mohammad Norouzi	2
+	Agile Autonomous Driving using End-to-End Deep Imitation Learning	2018	Yunpeng Pan Ching-An Cheng Kamil Saigol Keuntaek Lee Xinyan Yan Evangelos A. Theodorou Byron Boots	2
+ PDF Chat	End-to-End Learning of Driving Models with Surround-View Cameras and Route Planners	2018	Simon Hecker Dengxin Dai Luc Van Gool	2
+ PDF Chat	On Offline Evaluation of Vision-Based Driving Models	2018	Felipe Codevilla Antonio M. López Vladlen Koltun Alexey Dosovitskiy	2
+	ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the Worst	2019	Mayank Bansal Alex Krizhevsky Abhijit S. Ogale	2
+	Causal Confusion in Imitation Learning	2019	Pim de Haan Dinesh Jayaraman Sergey Levine	2
+	Sim-to-Real Robot Learning from Pixels with Progressive Nets	2016	Andrei A. Rusu Matej Vecerík Thomas Rothörl Nicolas Heess Razvan Pascanu Raia Hadsell	2
+	Safe Exploration in Markov Decision Processes	2012	Teodor Mihai Moldovan Pieter Abbeel	2
+ PDF Chat	On the Safety of Machine Learning: Cyber-Physical Systems, Decision Sciences, and Data Products	2017	Kush R. Varshney Homa Alemzadeh	2
+ PDF Chat	How Far are We from Solving Pedestrian Detection?	2016	Shanshan Zhang Rodrigo Benenson Mohamed Omran Jan Hosang Bernt Schiele	2
+ PDF Chat	End-to-End Driving Via Conditional Imitation Learning	2018	Felipe Codevilla Matthias Müller Antonio M. López Vladlen Koltun Alexey Dosovitskiy	2
+	A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning	2010	Stéphane Ross Geoffrey J. Gordon J. Andrew Bagnell	2
+	Adversarial Examples: Attacks and Defenses for Deep Learning	2019	Xiaoyong Yuan Pan He Qile Zhu Xiaolin Li	2
+	A Reinforcement Learning Based Approach for Automated Lane Change Maneuvers	2018	Pin Wang Ching‐Yao Chan Arnaud de La Fortelle	2
+ PDF Chat	Imminent Collision Mitigation with Reinforcement Learning and Vision	2018	Horia Porav Paul Newman	2
+ PDF Chat	Autonomous braking system via deep reinforcement learning	2017	Hyunmin Chae Chang Mook Kang ByeoungDo Kim Jaekyum Kim Chung Choo Chung Jun Won Choi	2
+ PDF Chat	MnasNet: Platform-Aware Neural Architecture Search for Mobile	2019	Mingxing Tan Bo Chen Ruoming Pang Vijay Vasudevan Mark Sandler Andrew Howard Quoc V. Le	2
+	Asynchronous Methods for Deep Reinforcement Learning	2016	Volodymyr Mnih Adrià Puigdomènech Badia Mehdi Mirza Alex Graves Tim Harley Timothy Lillicrap David Silver Koray Kavukcuoglu	2
+	Neural Architecture Search: A Survey	2019	Thomas Elsken Jan Hendrik Metzen Frank Hutter	2
+ PDF Chat	FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search	2019	Bichen Wu Kurt Keutzer Xiaoliang Dai Peizhao Zhang Yanghan Wang Fei Sun Yiming Wu Yuandong Tian Péter Vajda Yangqing Jia	2
+	Once-for-All: Train One Network and Specialize it for Efficient Deployment	2019	Han Cai Chuang Gan Tianzhe Wang Zhekai Zhang Song Han	2
+	Computer Vision for Autonomous Vehicles: Problems, Datasets and State of the Art	2020	Joel Janai Fatma Güney Aseem Behl Andreas Geiger	2
+ PDF Chat	Deep Reinforcement Learning: A Brief Survey	2017	Kai Arulkumaran Marc Peter Deisenroth Miles Brundage Anil A. Bharath	2
+	OnActor-Critic Algorithms	2003	Vijay R. Konda John N. Tsitsiklis	2
+ PDF Chat	Deep learning in neural networks: An overview	2014	Jürgen Schmidhuber	2
+	Sequence to Sequence Learning with Neural Networks	2014	Ilya Sutskever Oriol Vinyals Quoc V. Le	2
+	Practical Bayesian Optimization of Machine Learning Algorithms	2012	Jasper Snoek Hugo Larochelle Ryan P. Adams	2
+	Continuous control with deep reinforcement learning	2015	Timothy Lillicrap Jonathan J. Hunt Alexander Pritzel Nicolas Heess Tom Erez Yuval Tassa David Silver Daan Wierstra	2
+	Towards Adapting Deep Visuomotor Representations from Simulated to Real Environments.	2015	Eric Tzeng Coline Devin Judy Hoffman Chelsea Finn Xingchao Peng Sergey Levine Kate Saenko Trevor Darrell	2
+	End to End Learning for Self-Driving Cars	2016	Mariusz Bojarski Davide Del Testa Daniel Dworakowski Bernhard Firner Beat Flepp Prasoon Goyal Lawrence D. Jackel Mathew Monfort Urs Müller Jiakai Zhang	2
+ PDF Chat	A Survey of Motion Planning and Control Techniques for Self-Driving Urban Vehicles	2016	B. Paden Michal Čáp Sze Zheng Yong Dmitry Yershov Emilio Frazzoli	2
+	Query-Efficient Imitation Learning for End-to-End Autonomous Driving	2016	Jiakai Zhang Kyunghyun Cho	2