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From the 1 of 6 linked papers with an AI index.

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6 papers

eess.SY2026

Horizon Selection in Physics-Enhanced Neural ODEs: Theoretical Insights and Flux Linkage Application

Giulio Montecchio, Benjamin Hartmann, Sven Reimann +3

The paper investigates how the integration horizon used during training influences physics-enhanced Neural ODEs, proposing longer horizons to reduce bias in physical parameter esti…

eess.SY2026

Joint identification of permanent magnet synchronous machine and inverter

Giulio Montecchio, Sven Reimann, Benjamin Hartmann +3

In electric drive modeling, identifying the magnetic flux maps is essential for predicting accurately the torque, parameterizing a controller for tracking the torque or creating a…

cs.CV2024

Attention Normalization Impacts Cardinality Generalization in Slot Attention

Markus Krimmel, Jan Achterhold, Joerg Stueckler

Object-centric scene decompositions are important representations for downstream tasks in fields such as computer vision and robotics. The recently proposed Slot Attention module,…

cs.RO2024

Context-Conditional Navigation with a Learning-Based Terrain- and Robot-Aware Dynamics Model

Suresh Guttikonda, Jan Achterhold, Haolong Li +2

In autonomous navigation settings, several quantities can be subject to variations. Terrain properties such as friction coefficients may vary over time depending on the location of…

cs.LG2024

Explore the Context: Optimal Data Collection for Context-Conditional Dynamics Models

Jan Achterhold, Joerg Stueckler

In this paper, we learn dynamics models for parametrized families of dynamical systems with varying properties. The dynamics models are formulated as stochastic processes condition…

cs.RO2024

Learning a Terrain- and Robot-Aware Dynamics Model for Autonomous Mobile Robot Navigation

Jan Achterhold, Suresh Guttikonda, Jens U. Kreber +2

Mobile robots should be capable of planning cost-efficient paths for autonomous navigation. Typically, the terrain and robot properties are subject to variations. For instance, pro…