Abstract: Graph Neural Networks (GNNs) are proposed without considering the agnostic distribution shifts between training graphs and testing graphs, inducing the degeneration of the generalization ...

The recent past has seen an increasing interest in Heterogeneous Graph Neural Networks (HGNNs), since many real-world graphs are heterogeneous in nature, from citation graphs to email graphs. However, ...

Especially for those who prefer a minimalist aesthetic, the persistent presence of the volume and network icons can be a visual distraction. Recent updates to Windows 11, including the 24H2 release, ...

Department of Computer Science, Vanderbilt University, 2201 West End Ave, Nashville, Tennessee 37235, United States ...

She is also a Director of the Open Observatory of Network Interference (OONI), a nonprofit organization that provides free software tools and open data to empower the public to monitor and respond to ...

tensorflow를 사용하여 텍스트 전처리부터, Topic Models, BERT, GPT, LLM과 같은 최신 모델의 다운스트림 태스크들을 정리한 Deep Learning NLP 저장소입니다.

and reveals a novel neural-glia-fibroblast-lymphatic regulatory axis. This provides a new framework for understanding how the brain adapts its lymphatic network based on functional needs ...

Abstract: By integrating memristors into a Hopfield neural network (HNN), a diverse range of dynamical behavior can be generated, which has significant implications for modeling and biomimetic ...

The first Microsoft Research Fusion Summit brought together global experts to explore how AI can help unlock the potential of fusion energy. Discover how collaborations with leading institutions can ...

“The cap merely channels them into more opaque forms that cause damage to the network.” The debate centered on whether lifting the 80-byte OP_RETURN limit promotes transparency and simplifies ...