Our proposed VA-VAE (Vision foundation model Aligned Variational AutoEncoder) significantly expands the reconstruction-generation frontier of latent diffusion models, enabling faster convergence of ...

Therefore, this study proposes a sensor self-diagnosis design method based on the integration of binary convolutional autoencoder and Bayesian inference (BCAE-BI). First, to extract the redundancy ...

To overcome these limitations, the researchers implemented a deep learning approach using a Convolutional Variational Autoencoder (VAE) for compressing Ca II (8542 Å) spectral data. Their method ...

Ripple CEO Brad Garlinghouse said the SEC has finally pulled the plug on a four-year legal fight. Brad Garlinghouse didn’t bury the lede. “It’s over,” the CEO of Ripple declared in a video ...

Naive convolutional neural networks suffer from flawed structures in the frequency domain when predicting these radio maps, resulting in overly smoothed predictions. We propose a Spatial Frequency ...

In this work I create a variational auto-encoder to create trajectory query pairs for active preference learning of terrain costs for robot navigation.

Specifically, the figure shows the number of publications in dependence on the publication year for DL, deep learning; CNN, convolutional neural network; DBN, deep belief network; LSTM, long ...