iNNterpol: High-precision interpolation of stellar atmospheres with a deep neural network using a 1D convolutional auto encoder for feature extraction
Context. Given the widespread availability of grids of models for stellar atmospheres, it is necessary to recover intermediate atmospheric models by means of accurate techniques that go beyond simple linear interpolation and capture the intricacies of the data. Aims: Our goal is to establish a reliable, precise, lightweight, and fast method for
Westendorp Plaza, C. et al.
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7
2023