IEEE

Gen-GraphEx: Generative In-Distribution Graph Explanations for Time-Efficient Model-Level Interpretability of GNNs

Abstract: Graph neural networks (GNNs) have become the prevailing methodology for addressing graph data-related tasks, permeating critical domains like recommendation systems and drug development. The ...
GitHub

Unified Parallel Semantic Log Parsing based on Causal Graph Construction for Attack Attribution

# avoid python version conflict --- pyenv brew install pyenv-virtualenv brew install pyenv pyenv install 3.10 pyenv global 3.10 pyenv virtualenv 3.10 UTLParser # activate the environment eval "$(pyenv ...
GitHub

An easy-to-use bulk hold-time analyzer, generating graphs for the hold times of osu!standard replays.

To get started, head over to the latest release page on GitHub. From there, locate and download the ZIP file (ending with .zip). Once the download is complete, extract the ZIP file. On the first start ...
Hosted on MSN

Physics motion graphs: position, velocity, and time analysis

Learn how to analyze motion graphs in physics, including position-time and velocity-time graphs. This video explains slopes, areas, and motion behavior to help you clearly interpret real physics ...
IEEE

Dynamic Relation Graph Learning for Time-Aware Service Recommendation

Abstract: Driven by Service-Oriented Computing, time-aware service recommendation aims to support personalized mashup development, adapting to the rapid shifts of users’ dynamic preferences. Recently, ...
Business Insider

I went to CES to check out robotaxis. I left convinced that one player is far in the lead.

Business Insider's robotaxi reporter, Lloyd Lee, attended the biggest tech showcase of the year, CES, for the first time. News Chief Steve Russolillo chatted with Lee about what he learned on the ...