EGMS-QA Encoder

Pretrained encoder for EGMS displacement time series within 7 km tiles. It produces 256-dimensional point representations, which are spatially pooled into 65 tile tokens.

This repository contains the released weights, model settings, training recipe, and evaluation results.

Use the model

See the architecture on GitHub, then follow installation and a one-tile run to try the encoder. The same guide covers local inputs and training, resuming, and token extraction. Prepared tiles and precomputed tokens are available in the Dataset repository.

Files

file purpose
encoder.safetensors encoder weights
config.json model architecture and input dimensions
normalization.json input mean, standard deviation, and residual scale
training_args.json training recipe and checkpoint-selection record
eval_results.json masked-reconstruction metrics

Inference requires the weights, model config, and normalization. The Dataset repository provides the measurements and split manifest.

Input requirements

input or output contract
tile displacement vertical displacement in mm, [N,294]
coordinates EPSG:3035 easting and northing in meters, [N,2]
model preprocessing checkpoint normalization and centered coordinates
point representations [N,256]
pooled tokens [65,256] and a 65-element validity mask

The Dataset stores [0,294), corresponding to [8,302) on the 304-step source-preparation axis. Its data config retains the source offset and six-day cadence for physical-time calculations.

Use this checkpoint's normalization for inference. When training a new encoder on another corpus, fit normalization on that corpus's training split.

Evaluation

Evaluation covers 1,000 held-out tiles with 2,047,451 point histories. A central 88-step interval, approximately 30% of the 294-step input, is masked at the same positions for every point in a tile.

metric value
normalized MSE 0.0702
MSE 2.279 mm²
RMSE 1.510 mm
MAE 1.007 mm
pooled EGMS residual 1.433 mm
per-point RMSE P10 / P50 / P90 0.54 / 1.03 / 2.43 mm

These values describe reconstruction of held-out observations under the specified masking protocol.

Scope and license

The encoder consumes prepared EGMS-QA tiles. Official-product downloading, format conversion, and preparation of another reference period require a separate workflow. Its outputs describe observed deformation and do not establish causes, predict future motion, or certify structural safety.

The encoder is released under CC-BY-4.0.

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Dataset used to train risenyard/egms-qa-encoder

Collection including risenyard/egms-qa-encoder