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Protein Property Prediction Using Graph Neural Networks | Oxford Protein Informatics Group
| | foldingathome.org
Coronavirus - What we're doing and how you can help in simple terms - Folding@home
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| | anitagraser.com
GeoAI: key developments & insights | Free and Open Source GIS Ramblings
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| | It's been a while since my post on geo and the AI hype in 2019. Back then, I didn't use the term "GeoAI", even though it has certainly been around for a while (including, e.g., with dedicated SIGSPATIAL workshops since 2017). GeoAI isn't one single thing. It's an umbrella term, including: "AI for Geo" (using...
| | blog.fastforwardlabs.com
Exciting Applications of Graph Neural Networks
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| | Graph Neural Networks (GNNs) are neural networks that take graphs as inputs. These models operate on the relational information in data to produce insights not possible in other neural network architectures and algorithms. While there is much excitement in the deep learning community around GNNs, in industry circles, this is sometimes less so. So, I'll review a few exciting applications empowered by GNNs. Overview of Graphs and GNNs A graph (sometimes called a network) is a data structure that highlights the relationships between components in the data.
| | chrisroubis.com.au
The Future of Artificial Intelligence in Everyday Life - The Roubis Times
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| Artificial Intelligence (AI) is rapidly transforming our daily lives, influencing everything from how we communicate to how we shop and work. As technology a...