Sixty-three RNN models were tested with various hyperparameters, including optimizers and learning rates. Our findings indicate that GRU models achieve superior detection performance, particularly in ...

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) ...