The first time Twitter's algorithm was largely open-sourced was in 2023. Elon Musk, the billionaire owner of Tesla, had just ...

Abstract: For the interpretability of deep neural networks (DNNs) in visual-related tasks, existing explanation methods commonly generate a saliency map based on the linear relation between output ...

To make the tool more educational, we should display a brief explanation of the algorithm that is currently selected in the dropdown. This helps users understand what they are visualizing. Task: Use ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle the easiest pieces first. But this kind of sorting has a cost.

In cheminformatics, where machine learning is transforming our understanding of how molecular properties are predicted and explained, a critical challenge has long remained: making these powerful but ...

Abstract: Customer churn prediction is critical for businesses to retain customers and maintain revenue. In this paper, we compare three counterfactual explanation methods: Watcher's Method, Sphere ...

ABSTRACT: Missing data remains a persistent and pervasive challenge across a wide range of domains, significantly impacting data analysis pipelines, predictive modeling outcomes, and the reliability ...

When you’re trying to learn something new, it is useful to create desirable difficulties. You want to work hard without getting to the point of frustration. That work will signal to your brain that ...

Background: Early identification of infants with necrotizing enterocolitis (NEC) at risk of surgery is essential for an effective treatment. This study aims to clarify the risk factors of surgical NEC ...