Abstract: Equivariant quantum graph neural networks (EQGNNs) offer a potentially powerful method to process graph data. However, existing EQGNN models only consider the permutation symmetry of graphs, ...
This repository contains algorithms designed for map-based robot localization, specifically when dealing with maps composed of triangle meshes or complete scene graphs. These maps may be provided by ...
Abstract: Cross-modal 3D shape retrieval is a crucial and widely applied task in the field of 3D vision. Its goal is to construct retrieval representations capable of measuring the similarity between ...
Tracking 3D objects accurately and consistently is crucial for autonomous vehicles, enabling more reliable downstream tasks such as trajectory prediction and motion planning. Based on the substantial ...
"The no-kill-switch kind of thing? It's increasingly becoming a requirement," says Neo4j CEO Emil Eifrem. This is one of the reasons behind the company's decision to buy GraphAware, an intelligence ...
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