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 ...

In this paper, a signal-guided masked autoencoder (S-MAE) based semi-supervised learning framework is proposed for high-precision positioning with limited labeled channel impulse response (CIR) ...

A deep autoencoder (DAE)-based structure for end-to-end communication over the two-user Z-interference channel (ZIC) with finite-alphabet inputs is designed in ...