WebAug 14, 2024 · View. Show abstract. TeGraF: temporal and graph based fraudulent transaction detection framework. Conference Paper. Nov 2024. Shivshankar Reddy. Pranav Poduval. Anand Vir Singh Chauhan. Tanmoy ... WebGraph-based Deep Learning Literature The repository contains links primarily to conference publications in graph-based deep learning. The repository contains links also to Related Workshops, Surveys / Literature Reviews / Books, Software/Libraries.
Fairness-aware Graph Attention Networks IEEE …
WebInstead of designing hand-engineered features, graph representation learning has emerged to learn representations that can encode the abundant information about the graph. It … WebApr 27, 2024 · With the continuous penetration of artificial intelligence technologies, graph learning (i.e., machine learning on graphs) is gaining attention from both researchers and practitioners. Graph learning proves effective for many tasks, such as classification, link prediction, and matching. development adas driving function
Graph Database Conferences & Graph Technology Events …
WebApr 27, 2024 · Graphs are widely used as a popular representation of the network structure of connected data. Graph data can be found in a broad spectrum of application domains … WebMar 24, 2024 · Dec 10, 2024. In 30 mins, we are starting with the keynote of @TacoCohen! Taco will talk about two of the liveliest areas for the future of representation learning: - Category Theory - Causality Tune in to our … WebSelf-supervised Learning on Graphs. Self-supervised learning has a long history in machine learning and has achieved fruitful progresses in many areas, such as computer vision [35] and language modeling [9]. The traditional graph embedding methods [37, 14] define different kinds of graph proximity, i.e., the vertex proximity relationship, as ... churches in garden city kansas