<ul><li>A unified framework called Generalized Forward-Inverse (GFI) is proposed for subsurface imaging.</li><li>The framework aims to solve forward and inverse problems using deep learning techniques.</li><li>GFI encompasses previous works and introduces two new model architectures, Latent U-Net and Invertible X-Net.</li><li>The proposed models achieve state-of-the-art performance on synthetic datasets and show promise on real-world data.</li></ul>

A Unified Framework for Forward and Inverse Problems in Subsurface Imaging using Latent Space Translations

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