Image de couverture de livre

Tempering the Bayes Filter towards Improved Model-Based Estimation

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	van Zutphen, Menno, Herceg, Domagoj, Delimpaltadakis, Giannis, Antunes, Duarte J.
Format:	Preprint
Publié:	2025
Sujets:	Systems and Control Optimization and Control Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Beyond KL-divergence: Risk Aware Control Through Cross Entropy and Adversarial Entropy Regularization
par: van Zutphen, Menno, et autres
Publié: (2025)

Formal Entropy-Regularized Control of Stochastic Systems
par: van Zutphen, Menno, et autres
Publié: (2026)

Predictable Interval MDPs through Entropy Regularization
par: van Zutphen, Menno, et autres
Publié: (2024)

Distributionally Robust PAC-Bayesian Control
par: Herceg, Domagoj, et autres
Publié: (2026)

Abstracting the Traffic of Nonlinear Event-Triggered Control Systems
par: Delimpaltadakis, Giannis, et autres
Publié: (2020)

An Information Theory of Finite Abstractions and their Fundamental Scalability Limits
par: Delimpaltadakis, Giannis, et autres
Publié: (2025)

On the relationship between control barrier functions and projected dynamical systems
par: Delimpaltadakis, Giannis, et autres
Publié: (2023)

Formal Analysis of the Sampling Behaviour of Stochastic Event-Triggered Control
par: Delimpaltadakis, Giannis, et autres
Publié: (2022)

Continuous Approximations of Projected Dynamical Systems via Control Barrier Functions
par: Delimpaltadakis, Giannis, et autres
Publié: (2024)

Online Learning of Kalman Filtering: From Output to State Estimation
par: Ye, Lintao, et autres
Publié: (2026)

Feedback Optimization with State Constraints through Control Barrier Functions
par: Delimpaltadakis, Giannis, et autres
Publié: (2025)

Safe Feedback Optimization through Control Barrier Functions
par: Delimpaltadakis, Giannis, et autres
Publié: (2026)

Gradient Estimation and Variance Reduction in Stochastic and Deterministic Models
par: Keane, Ronan
Publié: (2024)

GreenLight-Gym: Reinforcement learning benchmark environment for control of greenhouse production systems
par: van Laatum, Bart, et autres
Publié: (2024)

A PAC-Bayes Approach for Controlling Unknown Linear Discrete-time Systems
par: Luo, Yujia, et autres
Publié: (2026)

Discrete fully probabilistic design: towards a control pipeline for the synthesis of policies from examples
par: Ferrentino, Enrico, et autres
Publié: (2021)

Improved Scalable Lipschitz Bounds for Deep Neural Networks
par: Syed, Usman, et autres
Publié: (2025)

The Silence that Speaks: Neural Estimation via Communication Gaps
par: Aggarwal, Shubham, et autres
Publié: (2025)

SINDy-RL: Interpretable and Efficient Model-Based Reinforcement Learning
par: Zolman, Nicholas, et autres
Publié: (2024)

Inverse Particle Filter
par: Singh, Himali, et autres
Publié: (2024)

Estimation Sample Complexity of a Class of Nonlinear Continuous-time Systems
par: Kuang, Simon, et autres
Publié: (2023)

ShieldNN: A Provably Safe NN Filter for Unsafe NN Controllers
par: Ferlez, James, et autres
Publié: (2020)

Safe and Robust Domains of Attraction for Discrete-Time Systems: A Set-Based Characterization and Certifiable Neural Network Estimation
par: Serry, Mohamed, et autres
Publié: (2026)

Data-driven Reachable Set Estimation with Tunable Adversarial and Wasserstein Distributional Guarantees
par: Pantazis, Georgios, et autres
Publié: (2026)

Inverse Unscented Kalman Filter
par: Singh, Himali, et autres
Publié: (2023)

Model-Based Diffusion for Trajectory Optimization
par: Pan, Chaoyi, et autres
Publié: (2024)

A Passivity-Based Method for Accelerated Convex Optimisation
par: Cho, Namhoon, et autres
Publié: (2023)

Provably-Stable Neural Network-Based Control of Nonlinear Systems
par: Li, Anran, et autres
Publié: (2025)

Dynamic Controlled Variables Based Dynamic Self-Optimizing Control
par: Zhou, Chenchen, et autres
Publié: (2026)

Verifying Closed-Loop Contractivity of Learning-Based Controllers via Partitioning
par: Davydov, Alexander
Publié: (2025)

Finite-Sample-Based Reachability for Safe Control with Gaussian Process Dynamics
par: Prajapat, Manish, et autres
Publié: (2025)

Distributionally Robust Regret Optimal Control Under Moment-Based Ambiguity Sets
par: Taha, Feras Al, et autres
Publié: (2025)

Learning-Based Optimal Control with Performance Guarantees for Unknown Systems with Latent States
par: Lefringhausen, Robert, et autres
Publié: (2023)

Differentiable Model Predictive Control on the GPU
par: Adabag, Emre, et autres
Publié: (2025)

Neural Network-assisted Interval Reachability for Systems with Control Barrier Function-Based Safe Controllers
par: Ajeyemi, Damola, et autres
Publié: (2025)

Semi-on-Demand Transit Feeders with Shared Autonomous Vehicles and Reinforcement-Learning-Based Zonal Dispatching Control
par: Ng, Max T. M., et autres
Publié: (2025)

Model Predictive Path Integral PID Control for Learning-Based Path Following
par: Kato, Teruki, et autres
Publié: (2026)

Learning Exactly Linearizable Deep Dynamics Models
par: Moriyasu, Ryuta, et autres
Publié: (2023)

Convex Chance-Constrained Stochastic Control under Uncertain Specifications with Application to Learning-Based Hybrid Powertrain Control
par: Kato, Teruki, et autres
Publié: (2026)

Operator Models for Continuous-Time Offline Reinforcement Learning
par: Hoischen, Nicolas, et autres
Publié: (2025)