A question from his granddaughter sparked Ed Scheinerman's new book, 'A Guide to Infinity', where he shows that infinity ...

When your AI assistant calculates revenue, bonuses, VAT or financial summaries, it isn’t doing math. It’s telling a convincing story about numbers.

Abstract: In multichannel electroencephalograph (EEG) emotion recognition, most graph-based studies employ shallow graph model for spatial characteristics learning due to node over-smoothing caused by ...

Pre-training Graph Model Phase. In the pre-training phase, we employ link prediction as the self-supervised task for pre-training the graph model. Producer Phase. In the Producer phase, we employ LLM ...

Abstract: Graph matching aims to establish node correspondences between graphs, which is a classic combinatorial optimization problem. In recent years, (deep) learning-based methods have emerged as a ...

Sign of the times: An AI agent autonomously wrote and published a personalized attack article against an open-source software maintainer after he rejected its code contribution. It might be the first ...

Raster-to-Graph is a novel automatic recognition framework, which achieves structural and semantic recognition of floorplans, addresses the problem of obtaining high-quality vectorized floorplans from ...