Abstract: Convolution on 3D point clouds is widely researched yet far from perfect in geometric deep learning. The traditional wisdom of convolution characterises feature correspondences ...

Abstract: Missing data in time series is a pervasive problem that serves as obstacles for subsequent traffic data analysis. Consequently, extensive research works have been conducted on traffic ...

DBB is a powerful ConvNet building block to replace regular conv. It improves the performance without any extra inference-time costs. This repo contains the code for building DBB and converting it ...

This work was published as: Conv-ViT: A Convolution and Vision Transformer-Based Hybrid Feature Extraction Method for Retinal OCT Classification Read the full paper here If you use this code or model ...

We get creative with an effects chain inspired by Jon Hopkins, and a heavy dose of felt piano ...

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From The Matrix to tangled wizard wars, these trilogies buried great ideas under lore, retcons, and endless explanations.

U.S. National Academies report on AI and the Future of Work, study co-chairs Tom Mitchell and Erik Brynjolfsson, November 2024. Whitepaper " How Can AI Accelerate Science, and How Can Our Government ...

Researchers have developed AdapGNN, a novel model-agnostic framework that addresses the oversmoothing problem in graph neural ...

Published in the Nature Electronics journal, researcher Sihong Wang likened the development to having a “personal, instantaneous doctor integrated into [users’] devices." Though it’s far from being ...