27 citations · 30 across the 9 of their papers we have counts for
3 papers · 1 filter
Learning Neural Feedback Linearization for Data-driven Systems via Augmented Lagrangian
Lakshmi Priya P. K., Andreas Schwung
The paper proposes a novel data-driven framework for designing and training a feedback linearizing controller by explicitly incorporating relative degree based conditions into the…
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…
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…