# Byron Boots

According to our database

Collaborative distances:

^{1}, Byron Boots authored at least 69 papers between 2005 and 2019.Collaborative distances:

## Timeline

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Book In proceedings Article PhD thesis Other## Links

#### On csauthors.net:

## Bibliography

2019

STEAP: simultaneous trajectory estimation and planning.

Auton. Robots, 2019

Robust Learning of Tactile Force Estimation through Robot Interaction.

Proceedings of the International Conference on Robotics and Automation, 2019

Joint Inference of Kinematic and Force Trajectories with Visuo-Tactile Sensing.

Proceedings of the International Conference on Robotics and Automation, 2019

Predictor-Corrector Policy Optimization.

Proceedings of the 36th International Conference on Machine Learning, 2019

Provably Efficient Imitation Learning from Observation Alone.

Proceedings of the 36th International Conference on Machine Learning, 2019

Adversarial Imitation via Variational Inverse Reinforcement Learning.

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

Truncated Back-propagation for Bilevel Optimization.

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Accelerating Imitation Learning with Predictive Models.

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Continuous-time Gaussian process motion planning via probabilistic inference.

I. J. Robotics Res., 2018

Fast Policy Learning through Imitation and Reinforcement.

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Learning-based Air Data System for Safe and Efficient Control of Fixed-wing Aerial Vehicles.

Proceedings of the 2018 IEEE International Symposium on Safety, 2018

Agile Autonomous Driving using End-to-End Deep Imitation Learning.

Proceedings of the Robotics: Science and Systems XIV, 2018

Learning and Inference in Hilbert Space with Quantum Graphical Models.

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Orthogonally Decoupled Variational Gaussian Processes.

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Differentiable MPC for End-to-end Planning and Control.

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Dual Policy Iteration.

Learning Generalizable Robot Skills from Demonstrations in Cluttered Environments.

Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

Semantically Meaningful View Selection.

Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

Optical Sensing and Control Methods for Soft Pneumatically Actuated Robotic Manipulators.

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Deep Forward and Inverse Perceptual Models for Tracking and Prediction.

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Sparse Gaussian Processes on Matrix Lie Groups: A Unified Framework for Optimizing Continuous-Time Trajectories.

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Initialization matters: Orthogonal Predictive State Recurrent Neural Networks.

Proceedings of the 6th International Conference on Learning Representations, 2018

Truncated horizon Policy Search: Combining Reinforcement Learning & Imitation Learning.

Proceedings of the 6th International Conference on Learning Representations, 2018

Improving Image Clustering With Multiple Pretrained CNN Feature Extractors.

Proceedings of the British Machine Vision Conference 2018, 2018

Learning Hidden Quantum Markov Models.

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Convergence of Value Aggregation for Imitation Learning.

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Learning to Align Images Using Weak Geometric Supervision.

Proceedings of the 2018 International Conference on 3D Vision, 2018

2017

Simultaneous Trajectory Estimation and Planning via Probabilistic Inference.

Proceedings of the Robotics: Science and Systems XIII, 2017

Exact Bounds on the Contact Driven Motion of a Sliding Object, With Applications to Robotic Pulling.

Proceedings of the Robotics: Science and Systems XIII, 2017

Predictive-State Decoders: Encoding the Future into Recurrent Networks.

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Predictive State Recurrent Neural Networks.

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Variational Inference for Gaussian Process Models with Linear Complexity.

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Information theoretic MPC for model-based reinforcement learning.

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Approximately optimal continuous-time motion planning and control via Probabilistic Inference.

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Motion planning with graph-based trajectories and Gaussian process inference.

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

4D crop monitoring: Spatio-temporal reconstruction for agriculture.

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction.

Proceedings of the 34th International Conference on Machine Learning, 2017

Prediction under Uncertainty in Sparse Spectrum Gaussian Processes with Applications to Filtering and Control.

Proceedings of the 34th International Conference on Machine Learning, 2017

Towards Robust Skill Generalization: Unifying Learning from Demonstration and Motion Planning.

Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017

One-Shot Learning for Semantic Segmentation.

Proceedings of the British Machine Vision Conference 2017, 2017

Learning from Conditional Distributions via Dual Embeddings.

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

Sampling Beats Fixed Estimate Predictors for Cloning Stochastic Behavior in Multiagent Systems.

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Learning to Smooth with Bidirectional Predictive State Inference Machines.

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Functional Gradient Motion Planning in Reproducing Kernel Hilbert Spaces.

Proceedings of the Robotics: Science and Systems XII, University of Michigan, Ann Arbor, Michigan, USA, June 18, 2016

Motion Planning as Probabilistic Inference using Gaussian Processes and Factor Graphs.

Proceedings of the Robotics: Science and Systems XII, University of Michigan, Ann Arbor, Michigan, USA, June 18, 2016

Incremental Variational Sparse Gaussian Process Regression.

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Simulation-based design of dynamic controllers for humanoid balancing.

Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016

Inference Machines for Nonparametric Filter Learning.

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Gaussian Process Motion planning.

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

Learning to Filter with Predictive State Inference Machines.

Proceedings of the 33nd International Conference on Machine Learning, 2016

The Nonparametric Kernel Bayes Smoother.

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Online Instrumental Variable Regression with Applications to Online Linear System Identification.

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Learning Latent Variable Models by Improving Spectral Solutions with Exterior Point Method.

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Incremental Sparse GP Regression for Continuous-Time Trajectory Estimation and Mapping.

Proceedings of the Robotics Research, 2015

Graph-Based Inverse Optimal Control for Robot Manipulation.

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

2014

Space-time functional gradient optimization for motion planning.

Proceedings of the 2014 IEEE International Conference on Robotics and Automation, 2014

Learning predictive models of a depth camera & manipulator from raw execution traces.

Proceedings of the 2014 IEEE International Conference on Robotics and Automation, 2014

2013

Hilbert Space Embeddings of Predictive State Representations.

Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

A Spectral Learning Approach to Range-Only SLAM.

Proceedings of the 30th International Conference on Machine Learning, 2013

2012

Two Manifold Problems with Applications to Nonlinear System Identification.

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

An Online Spectral Learning Algorithm for Partially Observable Nonlinear Dynamical Systems.

Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010

Reduced-Rank Hidden Markov Models.

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Closing the Learning-Planning Loop with Predictive State Representations.

Proceedings of the Robotics: Science and Systems VI, 2010

Predictive State Temporal Difference Learning.

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Hilbert Space Embeddings of Hidden Markov Models.

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Closing the learning-planning loop with predictive state representations.

Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), 2010

2008

Learning Cognitive Maps: Finding Useful Structure in an Uncertain World.

Proceedings of the Robotics and Cognitive Approaches to Spatial Mapping, 2008

2007

A Constraint Generation Approach to Learning Stable Linear Dynamical Systems.

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2005

DC-SSAT: A Divide-and-Conquer Approach to Solving Stochastic Satisfiability Problems Efficiently.

Proceedings of the Proceedings, 2005