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DEPARTMENTS

Emperical Interference

Haptic Intelligence

Modern Magnetic Systems

Perceiving Systems

Physical Intelligence

Robotic Materials

Social Foundations of Computation

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Autonomous Vision

Autonomous Learning

Bioinspired Autonomous Miniature Robots

Dynamic Locomotion

Embodied Vision

Human Aspects of Machine Learning

Intelligent Control Systems

Learning and Dynamical Systems

Locomotion in Biorobotic and Somatic Systems

Micro, Nano, and Molecular Systems

Movement Generation and Control

Neural Capture and Synthesis

Physics for Inference and Optimization

Organizational Leadership and Diversity

Probabilistic Learning Group

Topics

Robot Learning

Conference Paper

2022

Autonomous Learning

Robotics

AI

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Award

Learning and Dynamical Systems Conference Paper Continuous-time Lower Bounds for Gradient-based Algorithms Muehlebach, M., Jordan, M. I. In Proceedings of the International Conference on Machine Learning, 2020 (Published) URL BibTeX
Learning and Dynamical Systems Article Learning-based parametrized model predictive control for trajectory tracking Sferrazza, C., Muehlebach, M., D’Andrea, R. Optimal Control Application and Methods, 41(6):2225-2249, 2020 (Published) DOI BibTeX
Learning and Dynamical Systems Conference Paper A Dynamical Systems Perspective on Nesterov Acceleration Muehlebach, M., Jordan, M. I. In Proceedings of the International Conference on Machine Learning, 2019 (Published) URL BibTeX
Learning and Dynamical Systems Article A Method for Reducing the Complexity of Model Predictive Control in Robotics Applications Muehlebach, M., D’Andrea, R. IEEE Robotics and Automation Letters, 2019, 2019 (Published) URL BibTeX
Learning and Dynamical Systems Conference Paper Physics-informed Autoencoders for Lyapunov-stable Fluid Flow Prediction Erichson, N. B., M. Muehlebach, , Mahoney, M. In Machine Learning and the Physical Sciences Workshop, Conference on Neural Information Processing Systems, 2019 (Published) URL BibTeX
Learning and Dynamical Systems Technical Report The Silver Ratio and its Relation to Controllability Muehlebach, M. 2019 (Published) URL BibTeX