:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Massiani, Pierre-François, Fiedler, Christian, Haverbeck, Lukas, Solowjow, Friedrich, Trimpe, Sebastian
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2506.03898
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

On the Consistency of Kernel Methods with Dependent Observations
by: Massiani, Pierre-François, et al.
Published: (2024)

Viability of Future Actions: Robust Safety in Reinforcement Learning via Entropy Regularization
by: Massiani, Pierre-François, et al.
Published: (2025)

Safe Value Functions
by: Massiani, Pierre-François, et al.
Published: (2021)

Data-Driven Observability Analysis for Nonlinear Stochastic Systems
by: Massiani, Pierre-François, et al.
Published: (2023)

On Rollouts in Model-Based Reinforcement Learning
by: Frauenknecht, Bernd, et al.
Published: (2025)

Dyna-Style Safety Augmented Reinforcement Learning: Staying Safe in the Face of Uncertainty
by: Eisele, Artur, et al.
Published: (2026)

Event-Triggered Time-Varying Bayesian Optimization
by: Brunzema, Paul, et al.
Published: (2022)

On Foundation Models for Dynamical Systems from Purely Synthetic Data
by: Ziegler, Martin, et al.
Published: (2024)

On Safety in Safe Bayesian Optimization
by: Fiedler, Christian, et al.
Published: (2024)

Trust the Model Where It Trusts Itself -- Model-Based Actor-Critic with Uncertainty-Aware Rollout Adaption
by: Frauenknecht, Bernd, et al.
Published: (2024)

Safety in safe Bayesian optimization and its ramifications for control
by: Fiedler, Christian, et al.
Published: (2025)

Sailing Towards Zero-Shot State Estimation using Foundation Models Combined with a UKF
by: Holtmann, Tobin, et al.
Published: (2025)

Automatic nonlinear MPC approximation with closed-loop guarantees
by: Tokmak, Abdullah, et al.
Published: (2023)

CHEQ-ing the Box: Safe Variable Impedance Learning for Robotic Polishing
by: Cramer, Emma, et al.
Published: (2025)

MPX: Mixed Precision Training for JAX
by: Gräfe, Alexander, et al.
Published: (2025)

BayeSQP: Bayesian Optimization through Sequential Quadratic Programming
by: Brunzema, Paul, et al.
Published: (2026)

Contextualized Hybrid Ensemble Q-learning: Learning Fast with Control Priors
by: Cramer, Emma, et al.
Published: (2024)

Learning Hybrid Dynamics Models With Simulator-Informed Latent States
by: Ensinger, Katharina, et al.
Published: (2023)

Pseudo-rigid body networks: learning interpretable deformable object dynamics from partial observations
by: Mamedov, Shamil, et al.
Published: (2023)

Uncertainty-Aware Predictive Safety Filters for Probabilistic Neural Network Dynamics
by: Frauenknecht, Bernd, et al.
Published: (2026)

Learning to Race in Minutes: Infoprop Dyna on the Mini Wheelbot
by: Subhasish, Devdutt, et al.
Published: (2026)

Exact Inference for Continuous-Time Gaussian Process Dynamics
by: Ensinger, Katharina, et al.
Published: (2023)

Hierarchical Event-triggered Learning for Cyclically Excited Systems with Application to Wireless Sensor Networks
by: Beuchert, Jonas, et al.
Published: (2019)

Parameter-Adaptive Approximate MPC: Tuning Neural-Network Controllers without Retraining
by: Hose, Henrik, et al.
Published: (2024)

RockNet: Distributed Learning on Ultra-Low-Power Devices
by: Gräfe, Alexander, et al.
Published: (2025)

Concept Extraction for Time Series with ECLAD-ts
by: Holzapfel, Antonia, et al.
Published: (2025)

Biased Dreams: Limitations to Epistemic Uncertainty Quantification in Latent Space Models
by: Berger, Julia, et al.
Published: (2026)

A Systems-Theoretic View on the Convergence of Algorithms under Disturbances
by: Er, Guner Dilsad, et al.
Published: (2025)

Distributed Event-Based Learning via ADMM
by: Er, Guner Dilsad, et al.
Published: (2024)

Statistical Learning Theory for Distributional Classification
by: Fiedler, Christian
Published: (2026)

Tracking Object Positions in Reinforcement Learning: A Metric for Keypoint Detection (extended version)
by: Cramer, Emma, et al.
Published: (2023)

Asymptotic e-processes
by: Massiani, Pierre-François, et al.
Published: (2026)

Information-theoretic generalization bounds for learning from quantum data
by: Caro, Matthias, et al.
Published: (2023)

Local Preferential Bayesian Optimization
by: Menn, Johanna, et al.
Published: (2026)

Feedforward Controllers from Learned Dynamic Local Model Networks with Application to Excavator Assistance Functions
by: Greiser, Leon, et al.
Published: (2024)

Local Entropy Search over Descent Sequences for Bayesian Optimization
by: Stenger, David, et al.
Published: (2025)

Local Bayesian Optimization for Controller Tuning with Crash Constraints
by: von Rohr, Alexander, et al.
Published: (2024)

Combining Automated Optimisation of Hyperparameters and Reward Shape
by: Dierkes, Julian, et al.
Published: (2024)

Optimal structure learning and conditional independence testing
by: Gao, Ming, et al.
Published: (2025)

Approximate non-linear model predictive control with safety-augmented neural networks
by: Hose, Henrik, et al.
Published: (2023)