الباحثون

Soledad Villar

المنشورات 2

نسخة أولية وصول مفتوح

Warm-starting PDE solvers with any-dimensional machine learning

Wilson G. Gregory, George A. Kevrekidis, Ben Blum-Smith وآخرون · 2026

Any-dimensional machine learning models, such as graph neural networks (GNNs), can be naturally trained and evaluated on inputs of different sizes and dimensions. Inspired by the GNN transferability literature, we show mathematical conditions under which a partial differential equation (PDE) learning-based solver can b …

نسخة أولية وصول مفتوح

Transferable Graph Metanetworks

Yuxin Ma, Adir Dayan, Yam Eitan وآخرون · 2026

A weight space network (or metanetwork) takes the weights of another neural network as input and predicts properties of it. Most prior work trains such models on input networks of one or a few fixed sizes and evaluates them in-distribution. The few attempts at out-of-distribution size generalization remain limited in s …

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