Geostatistical Bias Injection Enhances Spatio-Temporal Forecasting with Transformers

This research explores a novel approach to enhance spatio-temporal forecasting by incorporating geostatistical covariance biases into self-attention mechanisms within transformers. The method aims to improve the accuracy and robustness of predictions in tasks involving spatially and temporally correlated data.

• •The paper proposes a method to improve spatio-temporal forecasting using spatially-informed transformers.
• •The core idea involves injecting geostatistical covariance biases.
• •This could lead to more accurate and reliable predictions in various applications.