| 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 | PRISM: 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 |
