An AI model from Michigan analyzes MRI studies with over 30 sequences in just three seconds on a single GPU – as accurate as ...

Researchers demonstrate fourfold improvement to LED steering results after enlisting the help of some good old-fashion AI Boffins at the Department of Energy's Sandia National Labs are working to ...

Abstract: Variational graph auto-encoders (VGAEs) are a key tool for node clustering, but existing models face several significant challenges. These challenges include a mismatch between inference and ...

Abstract: Recent 3D content generation pipelines commonly employ Variational Autoencoders (VAEs) to encode shapes into compact latent representations for diffusion-based generation. However, the ...

Encoders are a vital component in many applications that require motion control and feedback information. Whether a system’s requirement is speed, direction, or distance, an encoder produces control ...

Overview of our framework IM-Fuse (Incomplete Modality Fusion), (b) represents our Mamba Fusion Block (MFB) where learnable tokens are concatenated, and (c) depicts its interleaved version ...

This code provides an implementation of the Multivariate Variational Mode Decomposition (MVMD) algorithm (1). MVMD is used to decompose multivariate or multichannel data sets, enabling the analysis of ...