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arXiv Machine Learning By Yash Pincha, Andy Dimnaku, Andrew Chiang, Adarsh Ganeshram, Valentin Duruisseaux, Anima Anandkumar

Performance of Neural Operator Baselines on 'The Well' Dataset

Read the original on arXiv Machine Learning →

The Well is a 15‑terabyte benchmark covering 16 physical simulation domains, aimed at evaluating machine learning surrogate models for complex systems. Baseline neural operator results were presented as illustrative, with minimal hyperparameter tuning and a strict 12‑hour per‑run limit. A brief hyperparameter search on the Tucker‑factorized Fourier Neural Operator, using only a single input timestep, lowered VRMSE below most published baselines on 15 of 17 tasks, showing that modest tuning can dramatically improve performance.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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