Accurate estimation of two-dimensional (2D) multi-obstacle steady-state flows is crucial in various scientific and engineering disciplines, yet conventional methods often fall short in precision and ...

We propose a Crystal Diffusion Variational Autoencoder (CDVAE) that captures the physical inductive bias of material stability. By learning from the data distribution of stable materials, the decoder ...

Each method will be ranked based on selective performance measure in modeling healthy brain and the sensitivity towards domain shift. deep-neural-networks autoencoder anomaly-detection wasserstein-gan ...