Interpreting Graph Transformers for Long-Range Interactions is an attention-based explainer framework for graph transformers, taking inspiration from attention-based explainers for traditional NLP ...

Data can be presented in many ways that make it quicker and easier to read. In this section we will look at some of these ways. It is important to choose the best way to present data. A line graph can ...

Interpreting Graph Transformers for Long-Range Interactions proposes two explainability algorithms using learned attention matrices and integrated gradients. These explainability methods are built ...

In this seminar, we present an interpretable graph representation through a learning-based approach to predict if a model is worth training or not. We use an example of spiking neural network models ...

A line graph is an essential tool for displaying data trends over time, and it’s a great way to visualize information for comparison purposes. With just eight simple steps, anyone can create a clear ...

Bar charts and line graphs are both designed to help us visualize data. They are tools to convert numerical information into pictorial narratives that can be more easily comprehended. They don't ...

Abstract: EEG hyperscanning employs electroencephalography (EEG) activity to simultaneously monitor the brain activities of several individuals as they interact. During hyperscanning research, ...