To address these challenges, we propose a Noise-Consistent hypeRgraph AutoEncoder framework with denoising strategies, termed NCRAE, aimed at achieving robust node embeddings in ceRNA regulatory ...

Estimating the landscape and soil freeze-thaw (FT) dynamics in the Northern Hemisphere (NH) is crucial for understanding permafrost response to global warming and changes in regional and global carbon ...

To test this, we developed a compositional autoencoder (CAE) that decomposes high-dimensional data into distinct genotype-specific and environment-specific latent features. Our CAE framework employed ...

To the best of our knowledge, AstroMAE represents the first application of a masked autoencoder to astronomical data. By ignoring labels during the pretraining phase, the encoder gathers a general ...

This projects detect Anomalous Behavior through live CCTV camera feed to alert the police or local authority for faster response time. We are using Spatio Temporal AutoEncoder and more importantly ...

As an alternative, we trained modified autoencoder networks to mimic human-like behavior in a binaural detection task. The autoencoder architecture emphasizes interpretability and, hence, we “opened ...