activity
20242026
collaborators

5 papers

cs.LG2026

Layer-Specific Lipschitz Modulation for Fault-Tolerant Multimodal Representation Learning

Diyar Altinses, Andreas Schwung

Modern multimodal systems deployed in industrial and safety-critical environments must remain reliable under partial sensor failures, signal degradation, or cross-modal inconsisten…

cs.LG2026

Prior-Informed Neural Network Initialization: A Spectral Approach for Function Parameterizing Architectures

David Orlando Salazar Torres, Diyar Altinses, Andreas Schwung

Neural network architectures designed for function parameterization, such as the Bag-of-Functions (BoF) framework, bridge the gap between the expressivity of deep learning and the…

eess.SY2025

Luré-Postnikov Stability Analysis of Closed-Loop Control Systems with Gated Recurrent Neural Network-based Virtual Sensors

Eric Hilgert, Andreas Schwung

This article addresses certification of closed-loop stability when a virtual-sensor based on a gated recurrent neural network operates in the feedback path of a nonlinear control s…

cs.LG2025

Data driven feedback linearization of nonlinear control systems via Lie derivatives and stacked regression approach

Lakshmi Priya P. K., Andreas Schwung

Discovering the governing equations of a physical system and designing an effective feedback controller remains one of the most challenging and intensive areas of ongoing research.…

cs.LG2024

Predicting Wall Thickness Changes in Cold Forging Processes: An Integrated FEM and Neural Network approach

Sasa Ilic, Abdulkerim Karaman, Johannes Pöppelbaum +3

This study presents a novel approach for predicting wall thickness changes in tubes during the nosing process. Specifically, we first provide a thorough analysis of nosing processe…