Transmission Factors for Lossy Compression of PDE Training Data: Measuring What Reaches a Trained Operator
Operator-learning benchmarks ship as full-precision arrays, and they have grown to terabyte scale. A curator who wants to distribute one has to decide how coarsely to store it. That decision is usually made by fixing a tolerance on the reconstruction error of the stored field. We show that this quantity is measured in the wrong place. It compares the stored field with the original, before any model is trained. What the curator is buying is the accuracy of a model trained on the compressed copy, and the two can disagree: two PDEBench families stored to identical field error differ threefold downstream. A solution operator smooths, so only part of the codec error ever reaches the model's ou...
| Authors | Huy Hoang Le |
|---|---|
| Primary category | cs.LG |
| Published | 5 October 2026 |
| Last updated at source | 7 October 2026 |
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