Recent advances in Graph Convolutional Neural Networks (GCNNs) have shown their efficiency for nonEuclidean data on graphs, which often require a large amount of labeled data with high cost. It it ...

Official implementation of Discrete Diffusion Schrödinger Bridge Matching for Graph Transformation by Jun Hyeong Kim*, Seonghwan Kim*, Seokhyun Moon*, Hyeongwoo Kim*, Jeheon Woo*, Woo Youn Kim. [arXiv ...

The perception of the Chinese armed forces as outdated and relying only on numerical superiority is a serious mistake, ...

Experts point out that the use of a unified decoder will significantly enhance the efficiency and accuracy of scene graph generation. Compared to traditional methods ... that promoting this technology ...

The World Intelligent Industry Expo 2025 opened in Chongqing on September 5, focusing on the theme of "Artificial ...

Amid the chaos of revolutionary France, one man’s mathematical obsession gave way to a calculation that now underpins much of ...

Stagwell (NASDAQ: STGW), the challenger network built to transform marketing, announced the appointment of Slavi Samardzija as Chief Data and Platforms Officer at Stagwell, effective today. In this ...

An evergreen guide exploring the best Web3 crypto projects that are shaping the next generation of the internet ...

Agile rituals are great, but without tracking constraints and dependencies live, your transformation will stall.

This paper proposes a method of transferring physical continuous and switching/converter circuits working in continuous conduction mode (CCM) and discontinuous conduction mode (DCM) to graph ...