Preface

; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:1-7

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Automated Design of Grey-Box Recurrent Neural Networks For Fault Diagnosis using Structural Models and Causal Information

Daniel Jung; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:8-20

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PowerGym: A Reinforcement Learning Environment for Volt-Var Control in Power Distribution Systems

Ting-Han Fan, Xian Yeow Lee, Yubo Wang; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:21-33

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PRISM: Recurrent Neural Networks and Presolve Methods for Fast Mixed-integer Optimal Control

Abhishek Cauligi, Ankush Chakrabarty, Stefano Di Cairano, Rien Quirynen; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:34-46

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On the Effectiveness of Iterative Learning Control

Anirudh Vemula, Wen Sun, Maxim Likhachev, J. Andrew Bagnell; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:47-58

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Modeling Partially Observable Systems using Graph-Based Memory and Topological Priors

Steven Morad, Stephan Liwicki, Ryan Kortvelesy, Roberto Mecca, Amanda Prorok; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:59-73

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Noise Handling in Data-driven Predictive Control: A Strategy Based on Dynamic Mode Decomposition

Andrea Sassella, Valentina Breschi, Simone Formentin; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:74-85

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Learning-Enabled Robust Control with Noisy Measurements

Olle Kjellqvist, Anders Rantzer; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:86-96

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Joint Synthesis of Safety Certificate and Safe Control Policy Using Constrained Reinforcement Learning

Haitong Ma, Changliu Liu, Shengbo Eben Li, Sifa Zheng, Jianyu Chen; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:97-109

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Experience Replay with Likelihood-free Importance Weights

Samarth Sinha, Jiaming Song, Animesh Garg, Stefano Ermon; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:110-123

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Tracking and Planning with Spatial World Models

Baris Kayalibay, Atanas Mirchev, Patrick van der Smagt, Justin Bayer; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:124-137

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OpReg-Boost: Learning to Accelerate Online Algorithms with Operator Regression

Nicola Bastianello, Andrea Simonetto, Emiliano Dall’Anese; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:138-152

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Learning-based Moving Horizon Estimation through Differentiable Convex Optimization Layers

Simon Muntwiler, Kim P. Wabersich, Melanie N. Zeilinger; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:153-165

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Online No-regret Model-Based Meta RL for Personalized Navigation

Yuda Song, Yuan Ye, Wen Sun, Kris Kitani; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:166-179

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On the Sample Complexity of Stability Constrained Imitation Learning

Stephen Tu, Alexander Robey, Tingnan Zhang, Nikolai Matni; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:180-191

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Convergence Rates of Two-Time-Scale Gradient Descent-Ascent Dynamics for Solving Nonconvex Min-Max Problems

Thinh Doan; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:192-206

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Certified Robustness via Locally Biased Randomized Smoothing

Brendon G. Anderson, Somayeh Sojoudi; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:207-220

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Training Lipschitz Continuous Operators Using Reproducing Kernels

Henk van Waarde, Rodolphe Sepulchre; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:221-233

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Data-Enabled Gradient Flow as Feedback Controller: Regulation of Linear Dynamical Systems to Minimizers of Unknown Functions

Liliaokeawawa Cothren, Gianluca Bianchin, Emiliano Dall’Anese; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:234-247

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i-SpaSP: Structured Neural Pruning via Sparse Signal Recovery

Cameron R. Wolfe, Anastasios Kyrillidis; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:248-262

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Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling

Franck Djeumou, Cyrus Neary, Eric Goubault, Sylvie Putot, Ufuk Topcu; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:263-277

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Learning to Coordinate in Multi-Agent Systems: A Coordinated Actor-Critic Algorithm and Finite-Time Guarantees

Siliang Zeng, Tianyi Chen, Alfredo Garcia, Mingyi Hong; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:278-290

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Safe Reinforcement Learning with Chance-constrained Model Predictive Control

Samuel Pfrommer, Tanmay Gautam, Alec Zhou, Somayeh Sojoudi; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:291-303

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Accelerating Model-Free Policy Optimization Using Model-Based Gradient: A Composite Optimization Perspective

Yansong Li, Shuo Han; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:304-315

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Vision-based System Identification and 3D Keypoint Discovery using Dynamics Constraints

Miguel Jaques, Martin Asenov, Michael Burke, Timothy Hospedales; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:316-329

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Learning POMDP Models with Similarity Space Regularization: a Linear Gaussian Case Study

Yujie Yang, Jianyu Chen, Shengbo Li; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:330-341

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Distributed Stochastic Nash Equilibrium Learning in Locally Coupled Network Games with Unknown Parameters

Yuanhanqing Huang, Jianghai Hu; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:342-354

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Optimal Pointing Sequences in Spacecraft Formation Flying Using Online Planning with Resource Constraints

Samuel Low, Mykel Kochenderfer; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:355-365

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Traversing Time with Multi-Resolution Gaussian Process State-Space Models

Krista Longi, Jakob Lindinger, Olaf Duennbier, Melih Kandemir, Arto Klami, Barbara Rakitsch; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:366-377

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Data-Augmented Contact Model for Rigid Body Simulation

Yifeng Jiang, Jiazheng Sun, C. Karen Liu; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:378-390

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Gradient and Projection Free Distributed Online Min-Max Resource Optimization

Jingrong Wang, Ben Liang; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:391-403

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Online Estimation and Control with Optimal Pathlength Regret

Gautam Goel, Babak Hassibi; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:404-414

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Mixtures of Controlled Gaussian Processes for Dynamical Modeling of Deformable Objects

Ce Xu Zheng, Adriá Colomé, Luis Sentis, Carme Torras; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:415-426

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Learning Linear Models Using Distributed Iterative Hessian Sketching

Han Wang, James Anderson; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:427-440

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Data-Driven Safety Verification of Stochastic Systems via Barrier Certificates: A Wait-and-Judge Approach

Ali Salamati, Majid Zamani; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:441-452

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Learning to Reach, Swim, Walk and Fly in One Trial: Data-Driven Control with Scarce Data and Side Information

Franck Djeumou, Ufuk Topcu; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:453-466

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Data-driven Control of Unknown Linear Systems via Quantized Feedback

Feiran Zhao, Xingchen Li, Keyou You; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:467-479

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Adaptive Model Predictive Control by Learning Classifiers

Rel Guzman, Rafael Oliveira, Fabio Ramos; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:480-491

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MyoSuite: A Contact-rich Simulation Suite for Musculoskeletal Motor Control

Vittorio Caggiano, Huawei Wang, Guillaume Durandau, Massimo Sartori, Vikash Kumar; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:492-507

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Diffeomorphic Transforms for Generalised Imitation Learning

Weiming Zhi, Tin Lai, Lionel Ott, Fabio Ramos; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:508-519

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Total Energy Shaping with Neural Interconnection and Damping Assignment - Passivity Based Control

Santiago Sanchez-Escalonilla Plaza, Rodolfo Reyes-Baez, Bayu Jayawardhana; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:520-531

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Adversarially Robust Stability Certificates can be Sample-Efficient

Thomas Zhang, Stephen Tu, Nicholas Boffi, Jean-Jacques Slotine, Nikolai Matni; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:532-545

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Dynamic Learning of Correlation Potentials for a Time-Dependent Kohn-Sham System

Harish S. Bhat, Kevin Collins, Prachi Gupta, Christine M. Isborn; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:546-558

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Reinforcement Learning with Almost Sure Constraints

Agustin Castellano, Hancheng Min, Enrique Mallada, Juan Andrés Bazerque; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:559-570

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Distributed Neural Network Control with Dependability Guarantees: a Compositional Port-Hamiltonian Approach

Luca Furieri, Clara Lucía Galimberti, Muhammad Zakwan, Giancarlo Ferrari-Trecate; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:571-583

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Symplectic Momentum Neural Networks - Using Discrete Variational Mechanics as a prior in Deep Learning

Saul Santos, Monica Ekal, Rodrigo Ventura; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:584-595

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Adaptive Stochastic MPC under Unknown Noise Distribution

Charis Stamouli, Anastasios Tsiamis, Manfred Morari, George J. Pappas; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:596-607

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Block Contextual MDPs for Continual Learning

Shagun Sodhani, Franziska Meier, Joelle Pineau, Amy Zhang; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:608-623

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Formal Synthesis of Safety Controllers for Unknown Stochastic Control Systems using Gaussian Process Learning

Rameez Wajid, Asad Ullah Awan, Majid Zamani; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:624-636

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Improving Dynamic Regret in Distributed Online Mirror Descent Using Primal and Dual Information

Nima Eshraghi, Ben Liang; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:637-649

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Robust Data-Driven Output Feedback Control via Bootstrapped Multiplicative Noise

Benjamin Gravell, Iman Shames, Tyler Summers; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:650-662

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Input-to-State Stable Neural Ordinary Differential Equations with Applications to Transient Modeling of Circuits

Alan Yang, Jie Xiong, Maxim Raginsky, Elyse Rosenbaum; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:663-675

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Sample-based Distributional Policy Gradient

Rahul Singh, Keuntaek Lee, Yongxin Chen; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:676-688

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Clustering-based Mode Reduction for Markov Jump Systems

Zhe Du, Necmiye Ozay, Laura Balzano; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:689-701

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Learning Distributed Channel Access Policies for Networked Estimation: Data-driven Optimization in the Mean-field Regime

Marcos Vasconcelos; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:702-712

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Resiliency of Perception-Based Controllers Against Attacks

Amir Khazraei, Henry Pfister, Miroslav Pajic; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:713-725

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Safe Control with Minimal Regret

Andrea Martin, Luca Furieri, Florian Dörfler, John Lygeros, Giancarlo Ferrari-Trecate; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:726-738

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Safe Control with Neural Network Dynamic Models

Tianhao Wei, Changliu Liu; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:739-750

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Distributed Control using Reinforcement Learning with Temporal-Logic-Based Reward Shaping

Ningyuan Zhang, Wenliang Liu, Calin Belta; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:751-762

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Data-Driven Controller Synthesis of Unknown Nonlinear Polynomial Systems via Control Barrier Certificates

Ameneh Nejati, Bingzhuo Zhong, Marco Caccamo, Majid Zamani; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:763-776

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Neural Point Process for Learning Spatiotemporal Event Dynamics

Zihao Zhou, Xingyi Yang, Ryan Rossi, Handong Zhao, Rose Yu; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:777-789

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Data-Driven Chance Constrained Control using Kernel Distribution Embeddings

Adam Thorpe, Thomas Lew, Meeko Oishi, Marco Pavone; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:790-802

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Accelerating Dynamical System Simulations with Contracting and Physics-Projected Neural-Newton Solvers

Samuel Chevalier, Jochen Stiasny, Spyros Chatzivasileiadis; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:803-816

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Bounding the Difference Between Model Predictive Control and Neural Networks

Ross Drummond, Stephen Duncan, Mathew Turner, Patricia Pauli, Frank Allgower; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:817-829

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A Piecewise Learning Framework for Control of Unknown Nonlinear Systems with Stability Guarantees

Milad Farsi, Yinan Li, Ye Yuan, Jun Liu; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:830-843

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Adversarially Regularized Policy Learning Guided by Trajectory Optimization

Zhigen Zhao, Simiao Zuo, Tuo Zhao, Ye Zhao; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:844-857

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Time Varying Regression with Hidden Linear Dynamics

Horia Mania, Ali Jadbabaie, Devavrat Shah, Suvrit Sra; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:858-869

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Optimal Control with Learning on the Fly: System with Unknown Drift

Daniel Gurevich, Debdipta Goswami, Charles L. Fefferman, Clarence W. Rowley; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:870-880

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Barrier Bayesian Linear Regression: Online Learning of Control Barrier Conditions for Safety-Critical Control of Uncertain Systems

Lukas Brunke, Siqi Zhou, Angela P. Schoellig; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:881-892

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Can Foundation Models Perform Zero-Shot Task Specification For Robot Manipulation?

Yuchen Cui, Scott Niekum, Abhinav Gupta, Vikash Kumar, Aravind Rajeswaran; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:893-905

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Learning Reversible Symplectic Dynamics

Riccardo Valperga, Kevin Webster, Dmitry Turaev, Victoria Klein, Jeroen Lamb; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:906-916

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Robustness Certificates for Implicit Neural Networks: A Mixed Monotone Contractive Approach

Saber Jafarpour, Matthew Abate, Alexander Davydov, Francesco Bullo, Samuel Coogan; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:917-930

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ValueNetQP: Learned One-step Optimal Control for Legged Locomotion

Julian Viereck, Avadesh Meduri, Ludovic Righetti; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:931-942

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Sample Complexity of the Robust LQG Regulator with Coprime Factors Uncertainty

Yifei Zhang, Sourav Ukil, Ephraim Neimand, Serban Sabau, Myron Hohil; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:943-953

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Neighborhood Mixup Experience Replay: Local Convex Interpolation for Improved Sample Efficiency in Continuous Control Tasks

Ryan Sander, Wilko Schwarting, Tim Seyde, Igor Gilitschenski, Sertac Karaman, Daniela Rus; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:954-967

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Learning Spatio-Temporal Specifications for Dynamical Systems

Suhail Alsalehi, Erfan Aasi, Ron Weiss, Calin Belta; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:968-980

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Safe Autonomous Navigation for Systems with Learned SE(3) Hamiltonian Dynamics

Zhichao Li, Thai Duong, Nikolay Atanasov; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:981-993

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On the Heterogeneity of Independent Learning Dynamics in Zero-sum Stochastic Games

Muhammed Sayin, Kemal Cetiner; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:994-1005

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Deep Interactive Motion Prediction and Planning: Playing Games with Motion Prediction Models

Jose Luis Vazquez Espinoza, Alexander Liniger, Wilko Schwarting, Daniela Rus, Luc Van Gool; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:1006-1019

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Safety-Aware Preference-Based Learning for Safety-Critical Control

Ryan Cosner, Maegan Tucker, Andrew Taylor, Kejun Li, Tamas Molnar, Wyatt Ubelacker, Anil Alan, Gabor Orosz, Yisong Yue, Aaron Ames; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:1020-1033

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Convergence and Stability of the Stochastic Proximal Point Algorithm with Momentum

Junhyung Lyle Kim, Panos Toulis, Anastasios Kyrillidis; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:1034-1047

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Control-Tutored Reinforcement Learning: Towards the Integration of Data-Driven and Model-Based Control

Francesco De Lellis, Marco Coraggio, Giovanni Russo, Mirco Musolesi, Mario di Bernardo; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:1048-1059

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Neural Gaits: Learning Bipedal Locomotion via Control Barrier Functions and Zero Dynamics Policies

Ivan Dario Jimenez Rodriguez, Noel Csomay-Shanklin, Yisong Yue, Aaron D. Ames; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:1060-1072

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Robust Graph Neural Networks via Probabilistic Lipschitz Constraints

Raghu Arghal, Eric Lei, Shirin Saeedi Bidokhti; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:1073-1085

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A Simple and Efficient Sampling-based Algorithm for General Reachability Analysis

Thomas Lew, Lucas Janson, Riccardo Bonalli, Marco Pavone; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:1086-1099

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Sliding-Seeking Control: Model-Free Optimization with Safety Constraints

Felipe Galarza-Jiménez, Jorge Poveda, Emiliano Dall’Anese; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:1100-1111

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Generalization Bounded Implicit Learning of Nearly Discontinuous Functions

Bibit Bianchini, Mathew Halm, Nikolai Matni, Michael Posa; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:1112-1124

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Adaptive Variants of Optimal Feedback Policies

Brett Lopez, Jean-Jacques Slotine; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:1125-1136

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Learning Linear Complementarity Systems

Wanxin Jin, Alp Aydinoglu, Mathew Halm, Michael Posa; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:1137-1149

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Structure-Preserving Learning Using Gaussian Processes and Variational Integrators

Jan Brüdigam, Martin Schuck, Alexandre Capone, Stefan Sosnowski, Sandra Hirche; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:1150-1162

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Robust Online Control with Model Misspecification

Udaya Ghai, Xinyi Chen, Elad Hazan, Alexandre Megretski; Proceedings of The 4th Annual Learning for Dynamics and Control Conference, PMLR 168:1163-1175

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