Poster Session Program

Poster Session 1 (June 23, Thursday, 13:00-14:00)

Poster #	Paper #	Authors	Paper Title
1	33	Stephen Tu, Alexander Robey, Tingnan Zhang and Nikolai Matni	On the Sample Complexity of Stability Constrained Imitation Learning
2	110	Amir Khazraei, Henry Pfister and Miroslav Pajic	Resiliency of Perception-Based Controllers Against Attacks
3	146	Saber Jafarpour, Matthew Abate, Alexander Davydov, Francesco Bullo and Samuel Coogan	Robustness Certificates for Implicit Neural Networks: A Mixed Monotone Contractive Approach
4	7	Steven Morad, Stephan Liwicki, Ryan Kortvelesy, Roberto Mecca and Amanda Prorok	Modeling Partially Observable Systems using Graph-Based Memory and Topological Priors
5	6	Anirudh Vemula, Wen Sun, Maxim Likhachev and J. Andrew Bagnell	On the Effectiveness of Iterative Learning Control
6	4	Ting-Han Fan, Xian Yeow Lee and Yubo Wang	PowerGym: A Reinforcement Learning Environment for Volt-Var Control in Power Distribution Systems
7	54	Samuel Low	Optimizing Pointing Sequences with Resource Constraints in Large Satellite Formations using Reinforcement Learning
8	141	Daniel Gurevich, Debdipta Goswami, Charles L. Fefferman and Clarence W. Rowley	Optimal Control with Learning on the Fly: System with Unknown Drift
9	170	Thomas Lew, Lucas Janson, Riccardo Bonalli and Marco Pavone	A Simple and Efficient Sampling-based Algorithm for General Reachability Analysis
10	32	Yuda Song, Yuan Ye, Wen Sun and Kris Kitani	Online No-regret Model-Based Meta RL for Personalized Navigation
11	46	Yansong Li and Shuo Han	Accelerating Model-Free Policy Optimization Using Model-Based Gradient: A Composite Optimization Perspective
12	56	Yifeng Jiang, Jiazheng Sun and C. Karen Liu	Data-Augmented Contact Model for Rigid Body Simulation
13	160	Muhammed Sayin and Kemal Cetiner	On the Heterogeneity of Independent Learning Dynamics in Zero-sum Stochastic Games
14	147	Julian Viereck, Avadesh Meduri and Ludovic Righetti	ValueNetQP: Learned one-step optimal control for legged locomotion
15	117	Ningyuan Zhang, Wenliang Liu and Calin Belta	Distributed Control using Reinforcement Learning with Temporal-Logic-Based Reward Shaping
16	106	Zhe Du, Necmiye Ozay and Laura Balzano	Clustering-based Mode Reduction for Markov Jump Systems
17	87	Saul Santos, Monica Ekal and Rodrigo Ventura	Symplectic Momentum Neural Networks – Using Discrete Variational Mechanics as a prior in Deep Learning
18	88	Charis Stamouli, Anastasios Tsiamis, Manfred Morari and George J. Pappas	Adaptive Stochastic MPC under Unknown Noise Distribution
19	34	Thinh Doan	Convergence Rates of Two-Time-Scale Gradient Descent-Ascent Dynamics for Solving Nonconvex Min-Max Problems
20	113	Tianhao Wei and Changliu Liu	Safe Control with Neural Network Dynamic Models
21	148	Yifei Zhang, Sourav Ukil, Ephraim Neimand, Serban Sabau and Myron Hohil	Sample Complexity of the Robust LQG Regulator with Coprime Factors Uncertainty
22	108	Marcos Vasconcelos	Learning distributed channel access policies for networked estimation: data-driven optimization in the mean-field regime
23	73	Vittorio Caggiano, Huawei Wang, Guillaume Durandau, Massimo Sartori and Vikash Kumar	MyoSuite: A contact-rich simulation suite for musculoskeletal motor control
24	41	Franck Djeumou, Cyrus Neary, Eric Goubault, Sylvie Putot and Ufuk Topcu	Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling

Poster Session 2 (June 23, Thursday, 16:15-17:15)

Poster #	Paper #	Authors	Paper Title
1	19	Haitong Ma, Changliu Liu, Shengbo Eben Li, Sifa Zheng and Jianyu Chen	Joint Synthesis of Safety Certificate and Safe Control Policy using Constrained Reinforcement Learning
2	21	Samarth Sinha, Jiaming Song, Animesh Garg and Stefano Ermon	Experience Replay with Likelihood-free Importance Weights
3	40	Cameron R. Wolfe and Anastasios Kyrillidis	i-SpaSP: Structured Neural Pruning via Sparse Signal Recovery
4	51	Yuanhanqing Huang and Jianghai Hu	Distributed Stochastic Nash Equilibrium Learning in Locally Coupled Network Games with Unknown Parameters
5	94	Rameez Wajid, Asad Ullah Awan and Majid Zamani	Formal Synthesis of Safety Controllers for Unknown Stochastic Control Systems using Gaussian Process Learning
6	165	Ivan Dario Jimenez Rodriguez, Noel Csomay-Shanklin, Yisong Yue and Aaron D. Ames	Neural Gaits: Learning Bipedal Locomotion via Control Barrier Functions and Zero Dynamics Policies
7	1	Daniel Jung	Automated Design of Grey-Box Recurrent Neural Networks For Fault Diagnosis using Structural Models and Causal Information
8	17	Olle Kjellqvist and Anders Rantzer	Learning-Enabled Robust Control with Noisy Measurements
9	59	Gautam Goel and Babak Hassibi	Online estimation and control with optimal pathlength regret
10	69	Franck Djeumou and Ufuk Topcu	Learning How to Reach, Swim, Walk and Fly in One Trial: Control of Unknown Systems with Scarce Data and Side Information
11	83	Agustin Castellano, Hancheng Min, Enrique Mallada and Juan Andrés Bazerque	Reinforcement Learning with Almost Sure Constraints
12	142	Lukas Brunke, Siqi Zhou and Angela P. Schoellig	Barrier Bayesian Linear Regression: Online Learning of Control Barrier Conditions for Safety-Critical Control of Uncertain Systems
13	180	Brett Lopez and Jean-Jacques Slotine	Adaptive Variants of Optimal Feedback Policies
14	167	Raghu Arghal, Eric Lei and Shirin Saeedi Bidokhti	Robust Graph Neural Networks via Probabilistic Lipschitz Constraints
15	143	Yuchen Cui, Scott Niekum, Abhinav Gupta, Vikash Kumar and Aravind Rajeswaran	Can Foundation Models Perform Zero-Shot Task Specification For Robot Manipulation?
16	70	Feiran Zhao, Xingchen Li and Keyou You	Data-driven Control of Unknown Linear Systems via Quantized Feedback
17	61	Ce Xu Zheng, Adrià Colomé, Luis Sentis and Carme Torras	Mixtures of Controlled Gaussian Processes for Dynamical Modeling of Deformable Objects
18	78	Santiago Sanchez-Escalonilla Plaza, Rodolfo Reyes-Baez and Bayu Jayawardhana	Total Energy Shaping with Neural Interconnection and Damping Assignment – Passivity Based Control
19	163	Junhyung Lyle Kim, Panos Toulis and Anastasios Kyrillidis	Convergence and Stability of the Stochastic Proximal Point Algorithm with Momentum
20	171	Felipe Galarza-Jiménez, Jorge Poveda and Emiliano Dall’Anese	Sliding-Seeking Control:Model-Free Optimization with Hard Constraints
21	172	Bibit Bianchini, Mathew Halm, Nikolai Matni and Michael Posa	Generalization Bounds for Implicit Learning of Nearly Discontinuous Functions
22	5	Abhishek Cauligi, Ankush Chakrabarty, Stefano Di Cairano and Rien Quirynen	Recurrent Neural Networks and Presolve Methods for Fast Mixed-integer Optimal Control
23	93	Shagun Sodhani, Franziska Meier, Joellw Pineau and Amy Zhang	Block Contextual MDPs for Continual Learning
24	162	Ryan Cosner, Maegan Tucker, Andrew Taylor, Kejun Li, Tamas Molnar, Wyatt Ubelacker, Anil Alan, Gabor Orosz, Yisong Yue and Aaron Ames	Safety-Aware Preference-Based Learning for Safety-Critical Control

Poster Session 3 (June 24, Friday, 11:00-12:00)

Poster #	Paper #	Authors	Paper Title
1	86	Luca Furieri, Clara Lucía Galimberti, Muhammad Zakwan and Giancarlo Ferrari-Trecate	Distributed neural network control with dependability guarantees: a compositional port-Hamiltonian approach
2	140	Horia Mania, Ali Jadbabaie, Devavrat Shah and Suvrit Sra	Time varying regression with hidden linear dynamics
3	144	Riccardo Valperga, Kevin Webster, Dmitry Turaev, Victoria Klein and Jeroen Lamb	Structure-preserving time-reversible symplectic neural networks for learning dynamical systems
4	55	Krista Longi, Jakob Lindinger, Olaf Duennbier, Melih Kandemir, Arto Klami and Barbara Rakitsch	Traversing Time with Multi-Resolution Gaussian Process State-Space Models
5	68	Ali Salamati and Majid Zamani	Data-Driven Safety Verification of Stochastic Systems via Barrier Certificates: A Wait-and-Judge Approach
6	72	Rel Guzman, Rafael Oliveira and Fabio Ramos	Adaptive Model Predictive Control by Learning Classifiers
7	79	Thomas Zhang, Stephen Tu, Nicholas Boffi, Jean-Jacques Slotine and Nikolai Matni	Adversarially Robust Stability Certificates can be Sample-Efficient
8	80	Harish S. Bhat, Kevin Collins, Prachi Gupta and Christine M. Isborn	Dynamic Learning of Correlation Potentials for a Time-Dependent Kohn-Sham System
9	99	Alan Yang, Jie Xiong, Maxim Raginsky and Elyse Rosenbaum	Input-to-State Stable Neural Ordinary Differential Equations with Applications to Transient Modeling of Circuits
10	112	Andrea Martin, Luca Furieri, Florian Dörfler, John Lygeros and Giancarlo Ferrari Trecate	Safe Control with Minimal Regret
11	161	Jose Luis Vazquez Espinoza, Alexander Liniger, Wilko Schwarting, Daniela Rus and Luc Van Gool	Deep Interactive Motion Prediction and Planning: Playing Games with Motion Prediction Models
12	126	Adam Thorpe, Thomas Lew, Meeko Oishi and Marco Pavone	Data-Driven Chance Constrained Control using Kernel Distribution Embeddings
13	154	Zhichao Li, Thai Duong and Nikolay Atanasov	Safe Autonomous Navigation for Systems with Learned SE(3) Hamiltonian Dynamics
14	103	Rahul Singh, Keuntaek Lee and Yongxin Chen	Sample-based Distributional Policy Gradient
15	181	Wanxin Jin, Alp Aydinoglu, Mathew Halm and Michael Posa	Learning Linear Complementarity Systems
16	182	Jan Brüdigam, Martin Schuck, Alexandre Capone, Stefan Sosnowski and Sandra Hirche	Structure-Preserving Learning Using Gaussian Processes and Variational Integrators
17	151	Ryan Sander, Wilko Schwarting, Tim Seyde, Igor Gilitschenski, Sertac Karaman and Daniela Rus	Neighborhood Mixup Experience Replay: Local Convex Interpolation for Improved Sample Efficiency in Continuous Control Tasks
18	152	Suhail Alsalehi, Erfan Aasi, Ron Weiss and Calin Belta	Learning Spatio-Temporal Specifications for Dynamical Systems
19	37	Henk van Waarde and Rodolphe Sepulchre	Training Lipschitz continuous operators using reproducing kernels
20	42	Siliang Zeng, Tianyi Chen, Alfredo Garcia and Mingyi Hong	Learning to Coordinate in Multi-Agent Systems: A Coordinated Actor-Critic Algorithm and Finite-Time Guarantees
21	49	Yujie Yang, Jianyu Chen and Shengbo Li	Learning POMDP Models with Similarity Space Regularization: a Linear Gaussian Case Study
22	65	Han Wang and James Anderson	Learning Linear Models Using Distributed Iterative Hessian Sketching
23	16	Andrea Sassella, Valentina Breschi and Simone Formentin	Noise handling in data-driven predictive control: a strategy based on dynamic mode decomposition
24	129	Samuel Chevalier, Jochen Stiasny and Spyros Chatzivasileiadis	Accelerating Dynamical System Simulations with Contracting and Physics-Projected Neural-Newton Solvers

Poster Session 4 (June 24, Friday, 15:15 – 16:15)

Poster #	Paper #	Authors	Paper Title
1	48	Miguel Jaques, Martin Asenov, Michael Burke and Timothy Hospedales	Vision-based system identification and 3D keypoint discovery using dynamics constraints
2	76	Weiming Zhi, Tin Lai, Lionel Ott and Fabio Ramos	Diffeomorphic Transforms for Generalised Imitation Learning
3	27	Simon Muntwiler, Kim P. Wabersich and Melanie N. Zeilinger	Learning-based Moving Horizon Estimation through Differentiable Convex Optimization Layers
4	24	Baris Kayalibay, Atanas Mirchev, Patrick van der Smagt and Justin Bayer	Tracking and Planning with Spatial World Models
5	36	Brendon G. Anderson and Somayeh Sojoudi	Certified Robustness via Locally Biased Randomized Smoothing
6	124	Zihao Zhou, Xingyi Yang, Ryan Rossi, Handong Zhao and Rose Yu	Neural Point Process for Learning Spatiotemporal Event Dynamics
7	184	Udaya Ghai, Xinyi Chen, Elad Hazan and Alexandre Megretski	Robust Online Control with Model Misspecification
8	44	Samuel Pfrommer, Tanmay Gautam, Alec Zhou and Somayeh Sojoudi	Safe Reinforcement Learning with Chance-constrained Model Predictive Control
9	26	Nicola Bastianello, Andrea Simonetto and Emiliano Dall’Anese	OpReg-Boost: Learning to Accelerate Online Algorithms with Operator Regression
10	122	Ameneh Nejati, Bingzhuo Zhong, Marco Caccamo and Majid Zamani	Data-Driven Controller Synthesis of Unknown Nonlinear Polynomial Systems via Control Barrier Certificates
11	98	Benjamin Gravell, Iman Shames and Tyler Summers	Robust Data-Driven Output Feedback Control via Bootstrapped Multiplicative Noise
12	132	Ross Drummond, Stephen Duncan, Mathew Turner, Patricia Pauli and Frank Allgower	Bounding the difference between model predictive control and neural networks
13	138	Zhigen Zhao, Simiao Zuo, Tuo Zhao and Ye Zhao	Adversarially Regularized Policy Learning Guided by Trajectory Optimization
14	95	Nima Eshraghi and Ben Liang	Improving Dynamic Regret in Distributed Online Mirror Descent Using Primal and Dual Information
15	39	Liliaokeawawa Cothren, Gianluca Bianchin and Emiliano Dall’Anese	Data-enabled Gradient Flow as Feedback Controller: Regulation of Linear Dynamical Systems to Minimizers of Unknown Functions
16	57	Jingrong Wang and Ben Liang	Gradient and Projection Free Distributed Online Min-Max Resource Optimization
17	133	Milad Farsi, Yinan Li, Ye Yuan and Jun Liu	A Piecewise Learning Framework for Control of Nonlinear Systems with Stability Guarantees
18	164	Francesco De Lellis, Marco Coraggio, Giovanni Russo, Mirco Musolesi and Mario di Bernardo	Control-Tutored Reinforcement Learning: Towards the Integration of Data-Driven and Model-Based Control