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Angelica Aviles-Rivero

2 accepted papers

2026

Do Neural Operators Forget Geometry? The Forgetting Hypothesis in Deep Operator Learning

ICML 2026poster

Neural operators perform well on structured domains, yet their behaviour on irregular geometries remains poorly understood. We show that this limitation is not merely an encoding issue, but a depth-wise failure mode inherent to deep operator architectures. We formalise the *Geometric Forgetting Hypo…

Cited by 0SourceScholar
2020

Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems

ICML 2020poster

Plug-and-play (PnP) is a non-convex framework that combines ADMM or other proximal algorithms with advanced denoiser priors. Recently, PnP has achieved great empirical success, especially with the integration of deep learning-based denoisers. However, a key problem of PnP based approaches is that th…

Cited by 121SourcePDFScholar