Image de couverture de livre

Uncertainty Quantification Metrics for Deep Regression

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Lind, Simon Kristoffersson, Xiong, Ziliang, Forssén, Per-Erik, Krüger, Volker
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning Robotics
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Hinge-Wasserstein: Estimating Multimodal Aleatoric Uncertainty in Regression Tasks
par: Xiong, Ziliang, et autres
Publié: (2023)

Normalizing Flows are Capable Models for Bi-manual Visuomotor Policy
par: Li, Jialong, et autres
Publié: (2025)

Making the Flow Glow -- Robot Perception under Severe Lighting Conditions using Normalizing Flow Gradients
par: Lind, Simon Kristoffersson, et autres
Publié: (2024)

Collision Risk Estimation via Loss Prediction in End-to-End Autonomous Driving
par: Xiong, Ziliang, et autres
Publié: (2025)

CUQDS: Conformal Uncertainty Quantification under Distribution Shift for Trajectory Prediction
par: Huang, Huiqun, et autres
Publié: (2024)

Shifting Uncertainty to Critical Moments: Towards Reliable Uncertainty Quantification for VLA Model
par: Tang, Yanchuan, et autres
Publié: (2026)

Predicting Safety Misbehaviours in Autonomous Driving Systems using Uncertainty Quantification
par: Grewal, Ruben, et autres
Publié: (2024)

Continuous Normalizing Flows for Uncertainty-Aware Human Pose Estimation
par: Liu, Shipeng, et autres
Publié: (2025)

Data-driven Kinematic Modeling in Soft Robots: System Identification and Uncertainty Quantification
par: Jiang, Zhanhong, et autres
Publié: (2025)

MATTER: Multiscale Attention for Registration Error Regression
par: Liu, Shipeng, et autres
Publié: (2025)

Uncertainty-Aware Trajectory Prediction via Rule-Regularized Heteroscedastic Deep Classification
par: Manas, Kumar, et autres
Publié: (2025)

MaskVal: Simple but Effective Uncertainty Quantification for 6D Pose Estimation
par: Quentin, Philipp, et autres
Publié: (2024)

DRIVE Through the Unpredictability:From a Protocol Investigating Slip to a Metric Estimating Command Uncertainty
par: Samson, Nicolas, et autres
Publié: (2025)

Uncertainty Quantification for Deep Regression using Contextualised Normalizing Flows
par: Marco, Adriel Sosa, et autres
Publié: (2025)

An Intuitive Tutorial to Gaussian Process Regression
par: Wang, Jie
Publié: (2020)

Interpretable Robotic Friction Learning via Symbolic Regression
par: Scholl, Philipp, et autres
Publié: (2025)

Uncertainty-aware Reward Design Process
par: Yang, Yang, et autres
Publié: (2025)

Inverting Non-Injective Functions with Twin Neural Network Regression
par: Wetzel, Sebastian J.
Publié: (2026)

Exterior Penalty Policy Optimization with Penalty Metric Network under Constraints
par: Gao, Shiqing, et autres
Publié: (2024)

Physics-informed Temporal Difference Metric Learning for Robot Motion Planning
par: Ni, Ruiqi, et autres
Publié: (2025)

Pedestrian Behavior Prediction for Automated Driving: Requirements, Metrics, and Relevant Features
par: Herman, Michael, et autres
Publié: (2020)

Adaptive Planning with Generative Models under Uncertainty
par: Jutras-Dubé, Pascal, et autres
Publié: (2024)

Robust Adversarial Policy Optimization Under Dynamics Uncertainty
par: Kim, Mintae, et autres
Publié: (2026)

Adaptable Recovery Behaviors in Robotics: A Behavior Trees and Motion Generators(BTMG) Approach for Failure Management
par: Ahmad, Faseeh, et autres
Publié: (2024)

On Learning the Tail Quantiles of Driving Behavior Distributions via Quantile Regression and Flows
par: Tee, Jia Yu, et autres
Publié: (2023)

Handling Long-Term Safety and Uncertainty in Safe Reinforcement Learning
par: Günster, Jonas, et autres
Publié: (2024)

Uncertainty Comes for Free: Human-in-the-Loop Policies with Diffusion Models
par: He, Zhanpeng, et autres
Publié: (2025)

When to Act, Ask, or Learn: Uncertainty-Aware Policy Steering
par: Yuan, Jessie, et autres
Publié: (2026)

Adaptive Target Localization under Uncertainty using Multi-Agent Deep Reinforcement Learning with Knowledge Transfer
par: Alagha, Ahmed, et autres
Publié: (2025)

Efficient Sensor Placement from Regression with Sparse Gaussian Processes in Continuous and Discrete Spaces
par: Jakkala, Kalvik, et autres
Publié: (2023)

Enhanced Quantile Regression with Spiking Neural Networks for Long-Term System Health Prognostics
par: Poland, David J
Publié: (2025)

Temporal and Semantic Evaluation Metrics for Foundation Models in Post-Hoc Analysis of Robotic Sub-tasks
par: Salfity, Jonathan, et autres
Publié: (2024)

Beyond Euclidean Proximity: Repairing Latent World Models with Horizon-Matched Trajectory Reachability Metrics
par: Li, Liangyu, et autres
Publié: (2026)

From Inference Efficiency to Embodied Efficiency: Revisiting Efficiency Metrics for Vision-Language-Action Models
par: Li, Zhuofan, et autres
Publié: (2026)

Driving Through Uncertainty: Risk-Averse Control with LLM Commonsense for Autonomous Driving under Perception Deficits
par: Hu, Yuting, et autres
Publié: (2025)

MTF-Grasp: A Multi-tier Federated Learning Approach for Robotic Grasping
par: Zaland, Obaidullah, et autres
Publié: (2025)

UMLoc: Uncertainty-Aware Map-Constrained Inertial Localization with Quantified Bounds
par: Alharbi, Mohammed S., et autres
Publié: (2026)

Learning from Suboptimal Data in Continuous Control via Auto-Regressive Soft Q-Network
par: Liu, Jijia, et autres
Publié: (2025)

Lifelong Ensemble Learning based on Multiple Representations for Few-Shot Object Recognition
par: Kasaei, Hamidreza, et autres
Publié: (2022)

Uncertainty-Aware Deployment of Pre-trained Language-Conditioned Imitation Learning Policies
par: Wu, Bo, et autres
Publié: (2024)