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Found 3 papers, 2 papers with code
Predicting the Geothermal Gradient in Colombia: a Machine Learning Approach
Of particular interest is the case of Colombia, a country with abundant geothermal resources.
Generative Adversarial Neural Operators
The inputs to the generator are samples of functions from a user-specified probability measure, e. g., Gaussian random field (GRF), and the generator outputs are synthetic data functions.
Data-driven Accelerogram Synthesis using Deep Generative Models
Our approach extends the Wasserstein GAN formulation to allow for the generation of ground-motions conditioned on a set of continuous physical variables.
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