This repository contains the source code used in our paper titled Yihe Pang, Bin Liu. DisoFLAG: Accurate prediction of protein intrinsic disorder and its functions using graph-based interaction ...

Abstract: Open set recognition (OSR) problem has been a challenge in many machine learning (ML) applications, such as security. As new/unknown malware families occur regularly, it is difficult to ...

Before installation, it’s crucial to understand that Microsoft Graph is a RESTful web API that integrates various Microsoft services. You only need to authenticate once to access data across these ...

Corporations face key obstacles in their desire to push toward greater digital transformation; and corporate departments need to play a more significant role in driving toward corporate objectives, ...

In today's rapidly evolving business landscape, uncertainty has become one of the only certainties. Geopolitical tensions, economic volatility, trade disputes and technological disruption create a ...

The aim of this project is to provide a graph representation suitable for dynamic models, as they occur in probabilistic programming languages (e.g. with stochastic control flow, or model recursion).

Jane JaeYeon Pyo, a third-year Tepper School of Business doctoral student, has developed a way to measure the distances between financial statements and a novel method of interpreting them, offering a ...

Abstract: This study explores the use of Graph Neural Networks (GNNs) to classify enzyme functions using the ENZYMES dataset, which represents proteins and their interactions as graphs. The literature ...

Conclusions: This study represents a pioneering effort in using LLMs, particularly GPT-4.0, to construct a comprehensive sepsis knowledge graph. The innovative application of prompt engineering, ...

Consider this rapid shift: In 2023, 22% of HR functions reported experimenting with or using gen AI. A year later, that figure has soared to 41%, according to research from the Institute for Corporate ...