Florian A. Hölzl — accepted AI-conference papers

2026

Beyond Uniformity: Regularizing Implicit Neural Representations through a Lipschitz Lens

Julian McGinnis, Suprosanna Shit, Florian A. Hölzl, Paul Friedrich, Paul Büschl, Vasiliki Sideri-Lampretsa +5

ICLR 2026poster

Implicit Neural Representations (INRs) have shown great promise in solving inverse problems, but their lack of inherent regularization often leads to a trade-off between expressiveness and smoothness. While Lipschitz continuity presents a principled form of implicit regularization, it is often appli…

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2026

Optimizing Rank for High-Fidelity Implicit Neural Representations

Julian McGinnis, Florian A. Hölzl, Suprosanna Shit, Florentin Bieder, Paul Friedrich, Mark Mühlau +3

ICML 2026poster

Implicit Neural Representations (INRs) based on vanilla Multi-Layer Perceptrons (MLPs) are widely believed to be incapable of representing high-frequency content. This has directed research efforts towards architectural interventions, such as coordinate embeddings or specialized activation functions…

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2025

Gradient-Weight Alignment as a Train-Time Proxy for Generalization in Classification Tasks

Florian A. Hölzl, Daniel Rueckert, Georgios Kaissis

NeurIPS 2025poster

Robust validation metrics remain essential in contemporary deep learning, not only to detect overfitting and poor generalization, but also to monitor training dynamics. In the supervised classification setting, we investigate whether interactions between training data and model weights can yield suc…

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