Nonlinear analysis and control of a reaction wheel-based 3D inverted pendulum. - Michael Muehlebach; Gajamohan Mohanarajah; Raffaello D'Andrea (CDC, 2013)

The Cubli: A reaction wheel based 3D inverted pendulum. - Mohanarajah Gajamohan; Michael Muehlebach; Tobias Widmer; Raffaello D'Andrea (ECC, 2013)

A Fan-Based, Low-Frequent, Forced Oscillation Technique Apparatus. - Hannes Maes; Gerd Vandersteen; Michael Muehlebach; Clara M. Ionescu (IEEE Trans. Instrum. Meas., 2014)

LMI-based synthesis for distributed event-based state estimation. - Michael Muehlebach; Sebastian Trimpe (ACC, 2015)

Guaranteed ℋ2 performance in distributed event-based state estimation. - Michael Muehlebach; Sebastian Trimpe (EBCCSP, 2015)

Parametrized infinite-horizon model predictive control for linear time-invariant systems with input and state constraints. - Michael Muehlebach; Raffaello D'Andrea (ACC, 2016)

Approximation of continuous-time infinite-horizon optimal control problems arising in model predictive control. - Michael Muehlebach; Raffaello D'Andrea (CDC, 2016)

Application of an approximate model predictive control scheme on an unmanned aerial vehicle. - Matthias Hofer 003; Michael Muehlebach; Raffaello D'Andrea (ICRA, 2016)

Approximation of Continuous-Time Infinite-Horizon Optimal Control Problems Arising in Model Predictive Control - Supplementary Notes. - Michael Muehlebach; Raffaello D'Andrea (CoRR, 2016)

Basis functions design for the approximation of constrained linear quadratic regulator problems encountered in model predictive control. - Michael Muehlebach; Raffaello D'Andrea (CDC, 2017)

Trajectory tracking and iterative learning on an unmanned aerial vehicle using parametrized model predictive control. - Carmelo Sferrazza; Michael Muehlebach; Raffaello D'Andrea (CDC, 2017)

Implementation of a parametrized infinite-horizon model predictive control scheme with stability guarantees. - Michael Muehlebach; Carmelo Sferrazza; Raffaello D'Andrea (ICRA, 2017)

Nonlinear Analysis and Control of a Reaction-Wheel-Based 3-D Inverted Pendulum. - Michael Muehlebach; Raffaello D'Andrea (IEEE Trans. Control. Syst. Technol., 2017)

On the Approximation of Constrained Linear Quadratic Regulator Problems and their Application to Model Predictive Control - Supplementary Notes. - Michael Muehlebach; Raffaello D'Andrea (CoRR, 2018)

Distributed Event-Based State Estimation for Networked Systems: An LMI Approach. - Michael Muehlebach; Sebastian Trimpe (IEEE Trans. Autom. Control., 2018)

Accelerometer-Based Tilt Determination for Rigid Bodies With a Nonaccelerated Pivot Point. - Michael Muehlebach; Raffaello D'Andrea (IEEE Trans. Control. Syst. Technol., 2018)

A Dynamical Systems Perspective on Nesterov Acceleration. - Michael Muehlebach; Michael I. Jordan (ICML, 2019)

Physics-informed Autoencoders for Lyapunov-stable Fluid Flow Prediction. - N. Benjamin Erichson; Michael Muehlebach; Michael W. Mahoney (CoRR, 2019)

The Silver Ratio and its Relation to Controllability. - Michael Muehlebach (CoRR, 2019)

A Method for Reducing the Complexity of Model Predictive Control in Robotics Applications. - Michael Muehlebach; Raffaello D'Andrea (IEEE Robotics Autom. Lett., 2019)

Continuous-time Lower Bounds for Gradient-based Algorithms. - Michael Muehlebach; Michael I. Jordan (ICML, 2020)

Optimization with Momentum: Dynamical, Control-Theoretic, and Symplectic Perspectives. - Michael Muehlebach; Michael I. Jordan (J. Mach. Learn. Res., 2021)

Sampling without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization. - Aniket Das; Bernhard Schölkopf; Michael Muehlebach (NeurIPS, 2022)

A Learning-based Iterative Control Framework for Controlling a Robot Arm with Pneumatic Artificial Muscles. - Hao Ma; Dieter Büchler; Bernhard Schölkopf; Michael Muehlebach (Robotics: Science and Systems, 2022)

Robust Recurrent Neural Network to Identify Ship Motion in Open Water with Performance Guarantees - Technical Report. - Daniel Frank; Decky Aspandi-Latif; Michael Muehlebach; Benjamin Unger; Steffen Staab (CoRR, 2022)

On Constraints in First-Order Optimization: A View from Non-Smooth Dynamical Systems. - Michael Muehlebach; Michael I. Jordan (J. Mach. Learn. Res., 2022)

Orthogonal Directions Constrained Gradient Method: from non-linear equality constraints to Stiefel manifold. - Sholom Schechtman; Daniil Tiapkin; Michael Muehlebach; Éric Moulines (COLT, 2023)

Data-Efficient Online Learning of Ball Placement in Robot Table Tennis. - Philip Tobuschat; Hao Ma; Dieter Büchler; Bernhard Schölkopf; Michael Muehlebach (IROS, 2023)

Black-Box vs. Gray-Box: A Case Study on Learning Table Tennis Ball Trajectory Prediction with Spin and Impacts. - Jan Achterhold; Philip Tobuschat; Hao Ma; Dieter Büchler; Michael Muehlebach; Joerg Stueckler (L4DC, 2023)

A Dynamical Systems Perspective on Discrete Optimization. - Tong Guanchun; Michael Muehlebach (L4DC, 2023)

Online Learning under Adversarial Nonlinear Constraints. - Pavel Kolev; Georg Martius; Michael Muehlebach (NeurIPS, 2023)

Causal effect estimation from observational and interventional data through matrix weighted linear estimators. - Klaus-Rudolf Kladny; Julius von Kügelgen; Bernhard Schölkopf; Michael Muehlebach (UAI, 2023)

Accelerated First-Order Optimization under Nonlinear Constraints. - Michael Muehlebach; Michael I. Jordan (CoRR, 2023)

Adaptive Decision-Making with Constraints and Dependent Losses: Performance Guarantees and Applications to Online and Nonlinear Identification. - Michael Muehlebach (CoRR, 2023)

A Robust Open-source Tendon-driven Robot Arm for Learning Control of Dynamic Motions. - Simon Guist; Jan Schneider 007; Hao Ma; Vincent Berenz; Julian Martus; Felix Grüninger; Michael Mühlebach; Jonathan Fiene; Bernhard Schölkopf; Dieter Büchler (CoRR, 2023)

Reinforcement learning with model-based feedforward inputs for robotic table tennis. - Hao Ma; Dieter Büchler; Bernhard Schölkopf; Michael Muehlebach (Auton. Robots, 2023)

Bi-Level Motion Imitation for Humanoid Robots. - Wenshuai Zhao; Yi Zhao 014; Joni Pajarinen; Michael Muehlebach (CoRL, 2024)

Subgroup-Specific Risk-Controlled Dose Estimation in Radiotherapy. - Paul Fischer; Hannah Willms; Moritz Schneider; Daniela Thorwarth; Michael Muehlebach; Christian F. Baumgartner (MICCAI (10), 2024)

Conformal Performance Range Prediction for Segmentation Output Quality Control. - Anna M. Wundram; Paul Fischer; Michael Mühlebach; Lisa M. Koch; Christian F. Baumgartner (UNSURE@MICCAI, 2024)

Safe & Accurate at Speed with Tendons: A Robot Arm for Exploring Dynamic Motion. - Simon Guist; Jan Schneider 007; Hao Ma; Le Chen; Vincent Berenz; Julian Martus; Heiko Ott; Felix Grüninger; Michael Muehlebach; Jonathan Fiene; Bernhard Schölkopf; Dieter Büchler (Robotics: Science and Systems, 2024)

Towards a Systems Theory of Algorithms. - Florian Dörfler; Zhiyu He; Giuseppe Belgioioso; Saverio Bolognani; John Lygeros; Michael Muehlebach (CoRR, 2024)

Balancing a 3D Inverted Pendulum using Remote Magnetic Manipulation. - Jasan Zughaibi; Bradley J. Nelson; Michael Muehlebach (CoRR, 2024)

Primal Methods for Variational Inequality Problems with Functional Constraints. - Liang Zhang; Niao He; Michael Muehlebach (CoRR, 2024)

Gray-Box Nonlinear Feedback Optimization. - Zhiyu He; Saverio Bolognani; Michael Muehlebach; Florian Dörfler (CoRR, 2024)

Stochastic Online Optimization for Cyber-Physical and Robotic Systems. - Hao Ma; Melanie N. Zeilinger; Michael Muehlebach (CoRR, 2024)

Distributed Event-Based Learning via ADMM. - Guner Dilsad Er; Sebastian Trimpe; Michael Muehlebach (CoRR, 2024)

Toward a Systems Theory of Algorithms. - Florian Dörfler; Zhiyu He; Giuseppe Belgioioso; Saverio Bolognani; John Lygeros; Michael Muehlebach (IEEE Control. Syst. Lett., 2024)

Deep Backtracking Counterfactuals for Causally Compliant Explanations. - Klaus-Rudolf Kladny; Julius von Kügelgen; Bernhard Schölkopf; Michael Muehlebach (Trans. Mach. Learn. Res., 2024)

Adversarial Training for Defense Against Label Poisoning Attacks. - Melis Ilayda Bal; Volkan Cevher; Michael Muehlebach (ICLR, 2025)

Conformal Generative Modeling with Improved Sample Efficiency through Sequential Greedy Filtering. - Klaus-Rudolf Kladny; Bernhard Schölkopf; Michael Muehlebach (ICLR, 2025)

Controlling Participation in Federated Learning with Feedback. - Michael Cummins; Guner Dilsad Er; Michael Muehlebach (L4DC, 2025)

A Pontryagin Perspective on Reinforcement Learning. - Onno Eberhard; Claire Vernade; Michael Muehlebach (L4DC, 2025)

The Sample Complexity of Online Reinforcement Learning: A Multi-model Perspective. - Michael Muehlebach; Zhiyu He; Michael I. Jordan (CoRR, 2025)

Decision-Dependent Stochastic Optimization: The Role of Distribution Dynamics. - Zhiyu He; Saverio Bolognani; Florian Dörfler; Michael Muehlebach (CoRR, 2025)

Quantization-Free Autoregressive Action Transformer. - Ziyad Sheebaelhamd; Michael Tschannen; Michael Muehlebach; Claire Vernade (CoRR, 2025)

Partially Observable Reinforcement Learning with Memory Traces. - Onno Eberhard; Michael Muehlebach; Claire Vernade (CoRR, 2025)

Robust Feedback Optimization with Model Uncertainty: A Regularization Approach. - Winnie Chan; Zhiyu He; Keith Moffat; Saverio Bolognani; Michael Muehlebach; Florian Dörfler (CoRR, 2025)

Constraint-Aware Diffusion Guidance for Robotics: Real-Time Obstacle Avoidance for Autonomous Racing. - Hao Ma; Sabrina Bodmer; Andrea Carron; Melanie Nicole Zeilinger; Michael Muehlebach (CoRR, 2025)

ESLM: Risk-Averse Selective Language Modeling for Efficient Pretraining. - Melis Ilayda Bal; Volkan Cevher; Michael Muehlebach (CoRR, 2025)

Zeroth-Order Optimization Finds Flat Minima. - Liang Zhang; Bingcong Li; Kiran Koshy Thekumparampil; Sewoong Oh; Michael Muehlebach; Niao He (CoRR, 2025)

Dynamic Electromagnetic Navigation. - Jasan Zughaibi; Bradley J. Nelson; Michael Muehlebach (IEEE Robotics Autom. Lett., 2025)