Another year, another chip update. There isn't much new this year, but it's still a great laptop for most users.

Comorbidity—the co-occurrence of multiple diseases in a patient—complicates diagnosis, treatment, and prognosis. Understanding how diseases connect at a molecular level is crucial, especially in aging ...

Abstract: In Transformer-based hyperspectral image classification (HSIC), predefined positional encodings (PEs) are crucial for capturing the order of each input token. However, their typical ...

Abstract: Transformers are emerging as a powerful alternative to convolutional neural networks (CNNs) for hyperspectral image (HSI) classification. However, most existing approaches either neglect the ...

As a work exploring the existing trade-off between accuracy and efficiency in the context of point cloud processing, Point Transformer V3 (PTV3) has made significant advancements in computational ...

This project implements Vision Transformer (ViT) for image classification. Unlike CNNs, ViT splits images into patches and processes them as sequences using transformer architecture. It includes patch ...

Instead of using RoPE’s low-dimensional limited rotations or ALiBi’s 1D linear bias, FEG builds position encoding on a higher-dimensional geometric structure. The idea is simple at a high level: Treat ...