| 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 |
