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Using causal AI to amplify sustainability in the textile industry
With the textile industry facing mounting scrutiny over the environmental impacts of fast fashion, two researchers from ...
Understanding cause-effect relationships between variables is of primary interest in many fields of science. The standard method for determining such relationships uses randomized controlled ...
Understanding how the brain anticipates future states and transmits or reconstructs information remains a central challenge in neuroscience. This Research ...
Abstract: Effective fault detection of complex systems can significantly enhance safety, availability, and maintainability. Recently, graph neural networks (GNNs), which leverage spatial structures ...
ABSTRACT: This paper applies the interdisciplinary framework of Earth System Science (ESS) to analyze the complex socio-ecological crisis facing the agricultural sector in the Hashemite Kingdom of ...
Machine learning is the ability of a machine to improve its performance based on previous results. Machine learning methods enable computers to learn without being explicitly programmed and have ...
Abstract: Causality is a fundamental notion in science and engineering. It has attracted much interest across research communities in statistics, machine learning (ML), healthcare, and artificial ...
This repository contains the MATLAB code that accompanies the research paper: Leeman AP., Köhler J., Bennani S., Zeilinger MN. “Predictive safety filter using system level synthesis.” Proceedings of ...
1️⃣ We present an interesting attempt, as illustrated in the figure below: Using the latest GPT-4o large model to generate schematic cancer gene identification. It is undeniable that the LLM possesses ...
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