For three decades, functional neuroimaging (fMRI) has been shaping the understanding of the human brain. A major obstacle for ...

Researchers Matthew Golub, Belle Liu, and Jacob Sacks at the Paul G. Allen School for Computer Science & Engineering, have ...

Fluid–structure interaction (FSI) governs how flowing water and air interact with marine structures—from wind turbines to ...

Obtaining clearer functional MRI data about the brain and its disorders is possible using artificial intelligence, according ...

Abstract: This paper introduces V2Coder, a non-autoregressive vocoder based on hierarchical variational autoencoders (VAEs). The hierarchical VAE with hierarchically extended prior and approximate ...

Abstract: Analyzing radar signals is an important task in operating electronic support measure systems. The received signals in the real electromagnetic environment often originate from multiple ...

We introduce MAESTRO, a tailored adaptation of the Masked Autoencoder (MAE) framework that effectively orchestrates the use of multimodal, multitemporal, and multispectral Earth Observation (EO) data.

Uncover how an AI system developed at KAIST optimizes injection moulding processes and transfers critical knowledge to ...

Masked autoencoder has demonstrated its effectiveness in self-supervised point cloud learning. Considering that masking is a kind of corruption, in this work we explore a more general denoising ...