A new study, published today in Nature Communications, offers clues into how APOE isoforms differentially affect human ...

This step ensures that the model can detect anomalies at different scales. VAE Latent Representation: The multi-resolution features are fed into the VAE encoder to learn a probabilistic latent ...

In order to eliminate the dimensional influence between different features and improve the effectiveness of model training ... Between the encoder and decoder, the autoencoder learns the feature ...

One promising approach is the sparse autoencoder (SAE), a deep learning ... A single neuron might activate for thousands of different concepts, and a single concept might activate a broad range ...

Abstract: Sparse auto-encoders are useful for ... problem that leads to a predictive model invariant to the noise level at test time. In other words, the same pre-trained model is able to generalize ...

In this project, we employ an unsupervised process grounded in pre-trained Transformers-based Sequential Denoising Auto-Encoder (TSDAE ... The TSDAE model is bifurcated into two primary components: ...

Although attempts have been made to model bidirectional reflectance ... The method, which is based on a latent BRDF auto-encoder, can produce organic materials for 3D objects, enabling realistic ...