Papers
546 papers found
Growing Q-networks: Solving continuous control tasks with adaptive control resolution
Tim Seyde, Peter Werner, Wilko Schwarting et al.
Hacking predictors means hacking cars: Using sensitivity analysis to identify trajectory prediction vulnerabilities for autonomous driving security
Marsalis Gibson, David Babazadeh, Claire Tomlin et al.
Hamiltonian GAN
Christine Allen-Blanchette
How safe am I given what I see? Calibrated prediction of safety chances for image-controlled autonomy
Zhenjiang Mao, Carson Sobolewski, Ivan Ruchkin
HSVI-based online minimax strategies for partially observable stochastic games with neural perception mechanisms
Rui Yan, Gabriel Santos, Gethin Norman et al.
Improving sample efficiency of high dimensional Bayesian optimization with MCMC
Zeji Yi, Yunyue Wei, Chu Xin Cheng et al.
Increasing information for model predictive control with semi-Markov decision processes
Rémy Hosseinkhan Boucher, Stella Douka, Onofrio Semeraro et al.
Interpretable data-driven model predictive control of building energy systems using SHAP
Patrick Henkel, Tobias Kasperski, Phillip Stoffel et al.
Inverse optimal control as an errors-in-variables problem
Rahel Rickenbach, Anna Scampicchio, Melanie N. Zeilinger
In vivo learning-based control of microbial populations density in bioreactors
Sara Maria Brancato, Davide Salzano, Francesco De Lellis et al.
Lagrangian inspired polynomial estimator for black-box learning and control of underactuated systems
Giulio Giacomuzzo, Riccardo Cescon, Diego Romeres et al.
Learning and deploying robust locomotion policies with minimal dynamics randomization
Luigi Campanaro, Siddhant Gangapurwala, Wolfgang Merkt et al.
Learning-based rigid tube model predictive control
Yulong Gao, Shuhao Yan, Jian Zhou et al.
Learning flow functions of spiking systems
Miguel Aguiar, Amritam Das, Karl H. Johansson
Learning for CasADi: Data-driven Models in Numerical Optimization
Tim Salzmann, Jon Arrizabalaga, Joel Andersson et al.
Learning locally interacting discrete dynamical systems: Towards data-efficient and scalable prediction
Beomseok Kang, Harshit Kumar, Minah Lee et al.
Learning “look-ahead” nonlocal traffic dynamics in a ring road
Chenguang Zhao, Huan Yu
Learning robust policies for uncertain parametric Markov decision processes
Luke Rickard, Alessandro Abate, Kostas Margellos
Learning soft constrained MPC value functions: Efficient MPC design and implementation providing stability and safety guarantees
Nicolas Chatzikiriakos, Kim Peter Wabersich, Felix Berkel et al.
Learning to stabilize high-dimensional unknown systems using Lyapunov-guided exploration
Songyuan Zhang, Chuchu Fan
Learning true objectives: Linear algebraic characterizations of identifiability in inverse reinforcement learning
Mohamad Louai Shehab, Antoine Aspeel, Nikos Arechiga et al.
Leveraging Hamilton-Jacobi PDEs with time-dependent Hamiltonians for continual scientific machine learning
Paula Chen, Tingwei Meng, Zongren Zou et al.
Linearised data-driven LSTM-based control of multi-input HVAC systems
Andreas Hinderyckx, Florence Guillaume
Mapping back and forth between model predictive control and neural networks
Ross Drummond, Pablo Baldivieso, Giorgio Valmorbida