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Found 3 papers, 2 papers with code
MAGIC: Modular Auto-encoder for Generalisable Model Inversion with Bias Corrections
Scientists often model physical processes to understand the natural world and uncover the causation behind observations.
From Spectra to Biophysical Insights: End-to-End Learning with a Biased Radiative Transfer Model
Advances in machine learning have boosted the use of Earth observation data for climate change research.
A mixed model approach to drought prediction using artificial neural networks: Case of an operational drought monitoring environment
The ANN process itself uses the brute-force approach that automatically partitions the training data into 10 sub-samples, builds the ANN models in these samples and evaluates their performance using multiple metrics.
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