In a novel study, researchers from the Icahn School of Medicine at Mount Sinai introduced LoGoFunc, an advanced computational tool that predicts pathogenic gain- and loss-of-function variants ...

Find out why backpropagation and gradient descent are key to prediction in machine learning ... If we think of the loss function as being plotted on the graph, we want to move in increments ...

With industries increasingly adopting machine learning, it seems likely that knowledge graph technology will also evolve hand-in-hand. As well as being a useful format for feeding training data to ...

Graph kernels are computer functions that measure the similarity of pairs of graphs in machine learning applications but their complexity have posed a challenge to classical computing systems.

Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization by rapidly predicting molecular interactions and properties. For instance, ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More The cloud’s place in the data environment is growing, and ...

The paper elaborates on a technique for using knowledge graphs with machine learning; specifically, a branch of machine learning called reinforcement learning. This is something that holds great ...