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preCICE coupling framework Adapter for the Ice-sheet and Sea-level System Model (ISSM)

ZipGAN is a deep learning framework for compressing and decompressing 3D Direct Numerical Simulation (DNS) datasets of turbulent flows. It uses a Super-Resolution GAN to reconstruct full-resolution DNS fields from compressed (filtered + downsampled) representations, achieving compression ratios of up to 512x while preserving fine-scale turbulence features.

This project serves the purpose of evaluating the LLM-Evaluator, a tool designed to provide automatic feedback on exercises for further structural improvements.

Repository for studies with VH

A Probabilistic Load Forecasting Project