Image de couverture de livre

Inverting Non-Injective Functions with Twin Neural Network Regression

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteur principal:	Wetzel, Sebastian J.
Format:	Preprint
Publié:	2026
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

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

Physics Encoded Blocks in Residual Neural Network Architectures for Digital Twin Models
par: Zia, Muhammad Saad, et autres
Publié: (2024)

The Road to Learning Explainable Inverse Kinematic Models: Graph Neural Networks as Inductive Bias for Symbolic Regression
par: Pandey, Pravin, et autres
Publié: (2025)

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

Loss Function Considering Dead Zone for Neural Networks
par: Inami, Koki, et autres
Publié: (2024)

TwinVLA: Data-Efficient Bimanual Manipulation with Twin Single-Arm Vision-Language-Action Models
par: Im, Hokyun, et autres
Publié: (2025)

CN-CBF: Composite Neural Control Barrier Function for Safe Robot Navigation in Dynamic Environments
par: Derajić, Bojan, et autres
Publié: (2026)

ORN-CBF: Learning Observation-conditioned Residual Neural Control Barrier Functions via Hypernetworks
par: Derajić, Bojan, et autres
Publié: (2025)

Safe Neural Control for Non-Affine Control Systems with Differentiable Control Barrier Functions
par: Xiao, Wei, et autres
Publié: (2023)

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

Reinforcement Twinning for Hybrid Control of Flapping-Wing Drones
par: Poletti, Romain, et autres
Publié: (2025)

Behavior-Inspired Neural Networks for Relational Inference
par: Yang, Yulong, et autres
Publié: (2024)

Uncertainty Quantification Metrics for Deep Regression
par: Lind, Simon Kristoffersson, et autres
Publié: (2024)

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

Digital Twin Supervised Reinforcement Learning Framework for Autonomous Underwater Navigation
par: Mari, Zamirddine, et autres
Publié: (2025)

RAYEN: Imposition of Hard Convex Constraints on Neural Networks
par: Tordesillas, Jesus, et autres
Publié: (2023)

Extracting Forward Invariant Sets from Neural Network-Based Control Barrier Functions
par: Vaisi, Goli, et autres
Publié: (2025)

Efficient Motion Planning for Manipulators with Control Barrier Function-Induced Neural Controller
par: Yu, Mingxin, et autres
Publié: (2024)

Closed-Form Interpretation of Neural Network Classifiers with Symbolic Gradients
par: Wetzel, Sebastian Johann
Publié: (2024)

From Flies to Robots: Inverted Landing in Small Quadcopters with Dynamic Perching
par: Habas, Bryan, et autres
Publié: (2024)

Bridging the Reality Gap in Digital Twins with Context-Aware, Physics-Guided Deep Learning
par: Ma, Sizhe, et autres
Publié: (2025)

Variational Adaptive Noise and Dropout towards Stable Recurrent Neural Networks
par: Kobayashi, Taisuke, et autres
Publié: (2025)

Investigating Lagrangian Neural Networks for Infinite Horizon Planning in Quadrupedal Locomotion
par: Kotecha, Prakrut, et autres
Publié: (2025)

Use Digital Twins to Support Fault Diagnosis From System-level Condition-monitoring Data
par: Court, Killian Mc, et autres
Publié: (2024)

Towards Safe Learning-Based Non-Linear Model Predictive Control through Recurrent Neural Network Modeling
par: Clement, Mihaela-Larisa, et autres
Publié: (2026)

Morphological-Symmetry-Equivariant Heterogeneous Graph Neural Network for Robotic Dynamics Learning
par: Xie, Fengze, et autres
Publié: (2024)

How Many Training Samples Are Needed for the Inverse Kinematics Solutions by Artificial Neural Networks
par: Lim, Dong-Won
Publié: (2026)

Underwater Soft Fin Flapping Motion with Deep Neural Network Based Surrogate Model
par: Hamamatsu, Yuya, et autres
Publié: (2025)

RoboBallet: Planning for Multi-Robot Reaching with Graph Neural Networks and Reinforcement Learning
par: Lai, Matthew, et autres
Publié: (2025)

Orientation-Free Neural Network-Based Bias Estimation for Low-Cost Stationary Accelerometers
par: Levin, Michal, et autres
Publié: (2025)

Digital Twin-based Control Co-Design of Full Vehicle Active Suspensions via Deep Reinforcement Learning
par: Tsai, Ying-Kuan, et autres
Publié: (2025)

Digital Twin-Enhanced Wireless Indoor Navigation: Achieving Efficient Environment Sensing with Zero-Shot Reinforcement Learning
par: Li, Tao, et autres
Publié: (2023)

Closed-Form Interpretation of Neural Network Latent Spaces with Symbolic Gradients
par: Wetzel, Sebastian J., et autres
Publié: (2024)

An Interpretable Neural Control Network with Adaptable Online Learning for Sample Efficient Robot Locomotion Learning
par: Srisuchinnawong, Arthicha, et autres
Publié: (2025)

Hysteresis-Aware Neural Network Modeling and Whole-Body Reinforcement Learning Control of Soft Robots
par: Chen, Zongyuan, et autres
Publié: (2025)

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

Safe Value Functions
par: Massiani, Pierre-François, et autres
Publié: (2021)

DisGNet: A Distance Graph Neural Network for Forward Kinematics Learning of Gough-Stewart Platform
par: Zhu, Huizhi, et autres
Publié: (2024)

Learning Contact Dynamics through Touching: Action-conditional Graph Neural Networks for Robotic Peg Insertion
par: Yi, Zongyao, et autres
Publié: (2025)

Implementing TD3 to train a Neural Network to fly a Quadcopter through an FPV Gate
par: Thomas, Patrick, et autres
Publié: (2024)