Thefrantic calls from friends and clients are familiar during times of market stress. “Where will the market open?” “Should I ...
Abstract: When distribution shifts occur between testing and training graph data, out-of-distribution (OOD) samples undermine the performance of graph neural networks (GNNs). To improve adaptive OOD ...
Chris Impey has received funding from NASA, NSF, Howard Hughes Medical Institute, and the Templeton Foundation. If you look across space with a telescope, you’ll see countless galaxies, most of which ...
Abstract: Graph machine learning has been extensively studied in both academia and industry. Although booming with a vast number of emerging methods and techniques, most of the literature is built on ...
A monthly food distribution at Normal West high school often included staples such as potatoes and apples. A food pantry that serves hundreds of Bloomington-Normal residents each month is ending. One ...
Amentum Holdings, a recent spin-off of Jacobs, is taking the critical asset engineering contracting industry by storm, with many new huge government contracts in defense and nuclear. 411% earnings ...
GOOD (Graph OOD) is a graph out-of-distribution (OOD) algorithm benchmarking library depending on PyTorch and PyG to make develop and benchmark OOD algorithms easily. Currently, GOOD contains 11 ...
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 ...
In this valuable study, the authors analyze droplet size distributions of multiple protein condensates and their fit to a scaling ansatz, highlighting that they exhibit features of first- and ...
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