Brian Hou

According to our database, Brian Hou authored at least 18 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Multi-Sample Long Range Path Planning under Sensing Uncertainty for Off-Road Autonomous Driving.

Matt Schmittle, Rohan Baijal, Brian Hou, Siddhartha S. Srinivasa, Byron Boots

CoRR, 2024

2023

Robot Motion Planning with Uncertainty and Urgency

Brian Hou

PhD thesis, 2023

GuILD: Guided Incremental Local Densification for Accelerated Sampling-based Motion Planning.

Rosario Scalise, Aditya Mandalika, Brian Hou, Sanjiban Choudhury, Siddhartha S. Srinivasa

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

2022

Dynamic Replanning with Posterior Sampling.

Brian Hou, Siddhartha S. Srinivasa

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Stein Variational Probabilistic Roadmaps.

Alexander Lambert, Brian Hou, Rosario Scalise, Siddhartha S. Srinivasa, Byron Boots

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

2021

Guided Incremental Local Densification for Accelerated Sampling-based Motion Planning.

Aditya Mandalika, Rosario Scalise, Brian Hou, Sanjiban Choudhury, Siddhartha S. Srinivasa

CoRR, 2021

Bayesian Residual Policy Optimization: : Scalable Bayesian Reinforcement Learning with Clairvoyant Experts.

Gilwoo Lee, Brian Hou, Sanjiban Choudhury, Siddhartha S. Srinivasa

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

2020

Posterior Sampling for Anytime Motion Planning on Graphs with Expensive-to-Evaluate Edges.

Brian Hou, Sanjiban Choudhury, Gilwoo Lee, Aditya Mandalika, Siddhartha S. Srinivasa

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

2019

Bayesian Policy Optimization for Model Uncertainty.

Gilwoo Lee, Brian Hou, Aditya Mandalika, Jeongseok Lee, Sanjiban Choudhury, Siddhartha S. Srinivasa

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Sample-Efficient Learning of Nonprehensile Manipulation Policies via Physics-Based Informed State Distributions.

Lerrel Pinto, Aditya Mandalika, Brian Hou, Siddhartha S. Srinivasa

CoRR, 2018

Bayes-CPACE: PAC Optimal Exploration in Continuous Space Bayes-Adaptive Markov Decision Processes.

Gilwoo Lee, Sanjiban Choudhury, Brian Hou, Siddhartha S. Srinivasa

CoRR, 2018

Bayesian Policy Optimization for Model Uncertainty.

Gilwoo Lee, Brian Hou, Aditya Mandalika, Jeongseok Lee, Siddhartha S. Srinivasa

CoRR, 2018

2017

Efficient Motion Planning for Problems Lacking Optimal Substructure.

Oren Salzman, Brian Hou, Siddhartha S. Srinivasa

Proceedings of the Twenty-Seventh International Conference on Automated Planning and Scheduling, 2017

2016

Nifty Assignments.

Nick Parlante, Julie Zelenski, Baker Franke, Arvind Bhusnurmath, Karen Her, Kristen Gee, Eric D. Manley, Timothy Urness, Marvin Zhang, Brian Hou, John DeNero, Josh Hug, Kevin Wayne

Proceedings of the 47th ACM Technical Symposium on Computing Science Education, 2016

Fuzz Testing Projects in Massive Courses.

Sumukh Sridhara, Brian Hou, Jeffrey Lu, John DeNero

Proceedings of the Third ACM Conference on Learning @ Scale, 2016

Dex-Net 1.0: A cloud-based network of 3D objects for robust grasp planning using a Multi-Armed Bandit model with correlated rewards.

Jeffrey Mahler, Florian T. Pokorny, Brian Hou, Melrose Roderick, Michael Laskey, Mathieu Aubry, Kai Kohlhoff, Torsten Kröger, James J. Kuffner, Ken Goldberg

Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Privacy-preserving Grasp Planning in the Cloud.

Jeffrey Mahler, Brian Hou, Sherdil Niyaz, Florian T. Pokorny, Ramu Chandra, Ken Goldberg

Proceedings of the IEEE International Conference on Automation Science and Engineering, 2016

2015

Problems Before Solutions: Automated Problem Clarification at Scale.

Soumya Basu, Albert Wu, Brian Hou, John DeNero

Proceedings of the Second ACM Conference on Learning @ Scale, 2015