Papers
546 papers found
DLKoopman: A deep learning software package for Koopman theory
Sourya Dey, Eric William Davis
Efficient Reinforcement Learning Through Trajectory Generation
Wenqi Cui, Linbin Huang, Weiwei Yang et al.
End-to-End Learning to Warm-Start for Real-Time Quadratic Optimization
Rajiv Sambharya, Georgina Hall, Brandon Amos et al.
Equilibria of Fully Decentralized Learning in Networked Systems
Yan Jiang, Wenqi Cui, Baosen Zhang et al.
Failing with Grace: Learning Neural Network Controllers that are Boundedly Unsafe
Panagiotis Vlantis, Leila Bridgeman, Michael Zavlanos
FedSysID: A Federated Approach to Sample-Efficient System Identification
Han Wang, Leonardo Felipe Toso, James Anderson
Filter-Aware Model-Predictive Control
Baris Kayalibay, Atanas Mirchev, Ahmed Agha et al.
Frequency Domain Gaussian Process Models for $H^∞$ Uncertainties
Alex Devonport, Peter Seiler, Murat Arcak
Full Gradient Deep Reinforcement Learning for Average-Reward Criterion
Tejas Pagare, Vivek Borkar, Konstantin Avrachenkov
Guaranteed Conformance of Neurosymbolic Models to Natural Constraints
Kaustubh Sridhar, Souradeep Dutta, James Weimer et al.
Hierarchical Policy Blending As Optimal Transport
An Thai Le, Kay Hansel, Jan Peters et al.
Hybrid Multi-agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems
Tobias Enders, James Harrison, Marco Pavone et al.
Hybrid Systems Neural Control with Region-of-Attraction Planner
Yue Meng, Chuchu Fan
Hyperparameter Tuning of an Off-Policy Reinforcement Learning Algorithm for H∞ Tracking Control
Alireza Farahmandi, Brian C Reitz, Mark Debord et al.
Improving Gradient Computation for Differentiable Physics Simulation with Contacts
Yaofeng Desmond Zhong, Jiequn Han, Biswadip Dey et al.
In-Distribution Barrier Functions: Self-Supervised Policy Filters that Avoid Out-of-Distribution States
Fernando Castañeda, Haruki Nishimura, Rowan Thomas McAllister et al.
Interpreting Primal-Dual Algorithms for Constrained Multiagent Reinforcement Learning
Daniel Tabas, Ahmed S Zamzam, Baosen Zhang
Interval Reachability of Nonlinear Dynamical Systems with Neural Network Controllers
Saber Jafarpour, Akash Harapanahalli, Samuel Coogan
ISAACS: Iterative Soft Adversarial Actor-Critic for Safety
Kai-Chieh Hsu, Duy Phuong Nguyen, Jaime Fernàndez Fisac
Learning Coherent Clusters in Weakly-Connected Network Systems
Hancheng Min, Enrique Mallada
Learning Disturbances Online for Risk-Aware Control: Risk-Aware Flight with Less Than One Minute of Data
Prithvi Akella, Skylar X Wei, Joel W. Burdick et al.
Learning-enhanced Nonlinear Model Predictive Control using Knowledge-based Neural Ordinary Differential Equations and Deep Ensembles
Kong Yao Chee, M. Ani Hsieh, Nikolai Matni
Learning Locomotion Skills from MPC in Sensor Space
Majid Khadiv, Avadesh Meduri, Huaijiang Zhu et al.
Learning Object-Centric Dynamic Modes from Video and Emerging Properties
Armand Comas, Christian Fernandez Lopez, Sandesh Ghimire et al.
Learning on Manifolds: Universal Approximations Properties using Geometric Controllability Conditions for Neural ODEs
Karthik Elamvazhuthi, Xuechen Zhang, Samet Oymak et al.