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An overview by the U.S. Geological Survey shows the location of the Nuugaatsiaq landslide (yellow star) relative to five broadband seismic stations (pink triangles) within 500 km of the landslide. Nuugaatsiaq (NUUG) was impacted by the resulting tsunami the reached a height of 300 feet at sea, though it was much lower before it reached the village. The inset shows the geometry of the fjords relative to the landslide and Nuugaatsiaq. (Source: USGS)

Small quake clusters can’t hide from AI

August 24, 2020

A deep learning algorithm developed at Rice University analyzes data from a deadly landslide in Greenland to show how it may someday predict seismic events like earthquakes and volcanic eruptions.

Yingyan Lin, assistant professor of electrical and computer engineering

Early Bird uses 10 times less energy to train deep neural networks

May 18, 2020

Rice engineers have found a way to train deep neural networks for a fraction of the energy required today. Their Early Bird method finds key network connectivity patterns early in training.

Rice computer science graduate students Beidi Chen and Tharun Medini

Deep learning rethink overcomes major obstacle in AI industry

March 2, 2020

Rice University computer scientists have overcome a major obstacle in the burgeoning artificial intelligence industry.

reconstructed image of a 1-centimeter-tall numeral 7 that was hidden behind a corner

Cameras see around corners in real time with deep learning

January 17, 2020

Rice researchers and collaborators have created an imaging system that can see detailed objects around corners in real time.

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