WebOct 12, 2024 · This architecture can be extended to other performance indicators such as jitter or packet loss. To adapt to complex topology, reference [42] proposes an intelligent routing policy based on graph-aware deep learning (GADL), in which the improved graph-aware neural network can effectively learn topology information. The routing calculation … WebAug 18, 2024 · Graph technology provider, GraphAware, has developed an innovative way to use NLP that helps users find insight in their connected data fast. Their flagship software platform is Hume, a graph-powered insights engine. Hume ingests data from multiple sources and applies NLP among other transformation and enrichment workflows.
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Web1 day ago · Download a PDF of the paper titled NaviSTAR: Socially Aware Robot Navigation with Hybrid Spatio-Temporal Graph Transformer and Preference Learning, by Weizheng Wang and 3 other authors Download PDF Abstract: Developing robotic technologies for use in human society requires ensuring the safety of robots' navigation … WebMay 6, 2024 · ACL-2024 GCAN: Graph-aware Co-Attention Networks for Explainable Fake News Detection on Social Media. ... Based on the causal graph among entities, news contents, and news veracity, they separately model the contribution of each cause (entities and contents) during training. In the inference stage, they remove the direct effect of the … trust and corporate services
How Hume & KeyLines make levels of insight skyrocket
WebApr 13, 2024 · GAP: A Graph-aware Language Model Framework for Knowledge Graph-to-Text Generation Anthony Colas, Mehrdad Alvandipour, Daisy Zhe Wang Recent … WebApr 14, 2024 · In this section, we present the proposed MPGRec. Specifically, as illustrated in Fig. 1, based on a user-POI interaction graph, a novel memory-enhanced period-aware graph neural network is proposed to learn the user and POI embeddings.In detail, a period-aware gate mechanism is designed for the temporal locality to filter out information … Web1 day ago · Based on the travel demand inferred from the GPS data, we develop a new deep learning model, i.e., Situational-Aware Multi-Graph Convolutional Recurrent Network (SA-MGCRN), along with a model updating scheme to achieve real-time forecasting of travel demand during wildfire evacuations. The proposed methodological framework is tested in … trust and estate accounting software