Bio-inspired computer networks self-organise and learn

(PhysOrg.com) -- Powerful computers made up of physically separate modules, self-organising networks, and computing inspired by biological systems are three hot research topics coming together in one European project.

Oceanographers predict increase in phytoplankton by 2100

A neural network-driven Earth system model has led University of California, Irvine oceanographers to a surprising conclusion: phytoplankton populations will grow in low-latitude waters by the end of the 21st century.

Deeper insight into Higgs boson production using W bosons

Discovering the Higgs boson in 2012 was only the start. Physicists immediately began measuring its properties, an investigation that is still ongoing as they try to unravel if the Higgs mechanism is realized in nature as ...

Testing a machine learning approach to geophysical inversion

A common problem in the geosciences is the need to deduce unseen physical structure based on limited observations. For instance, a ground-penetrating radar observation attempts to infer underground structure without any in ...

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