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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★ 1 cited
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…
cs.LG2025★ 3 cited
Stabilizing Multimodal Autoencoders: A Theoretical and Empirical Analysis of Fusion Strategies
Diyar Altinses, Andreas Schwung
In recent years, the development of multimodal autoencoders has gained significant attention due to their potential to handle multimodal complex data types and improve model perfor…