Spatially distributed prediction of streamflow and nitrogen (N) export dynamics is essential for precision management of agricultural watersheds. To address this need, a team of researchers led by the ...

While retrieval-augmented generation is effective for simpler queries, advanced reasoning questions require deeper connections between information that exist across documents. They require a knowledge ...

High sparse Knowledge Graph is a key challenge to solve the Knowledge Graph Completion task. Due to the sparsity of the KGs, there are not enough first-order neighbors to learn the features of ...

In the realm of Artificial Intelligence (AI), knowledge graphs stand as a crucial innovation, particularly influential in areas like machine learning and natural language processing (NLP). These ...

Even though it probably affects our lives every single day, most of us have no idea what a “knowledge graph” is. Asking your favorite voice assistant what the weather will be like tomorrow? That’s ...

High-dimensional -omics data such as genomic, transcriptomic, and metabolomic data offer great promise in advancing precision medicine. In particular, such data have enabled the investigation of ...

Artificial intelligence is touching every aspect of how we engage with information (and much more) these days. Today, a startup building out a business based on one particular application of that — ...

The healthcare industry has no shortage of clinical knowledge. What it lacks is a reliable way to apply that knowledge ...