Variational autoencoders can be leveraged to provide an effective method of inversion that is both accurate and computationally efficient.
machine learning & AI
Distributed Sensing and Machine Learning Hone Seismic Listening
Fiber-optic cables can provide a wealth of detailed data on subsurface vibrations from a wide range of sources. Machine learning offers a means to make sense of it all.
Machine Learning Pinpoints Meteorite-Rich Areas in Antarctica
A new algorithm suggests that only a small fraction of meteorites present on the White Continent’s surface have been recovered to date.
Comparing Machine Learning Models for Earthquake Detection
A new study evaluated the performance of emerging deep learning models for earthquake detection, phase identification, and phase picking.
Neural Networks Can Identify Carbon Dioxide in Seismic Observations
By establishing a machine-driven approach to interpreting seismic observations of carbon dioxide injection, researchers hope to improve tracking of carbon capture and sequestration projects.
A New Mayflower, Named for the Past, Autonomously Navigates the Future
To commemorate the 400th anniversary of the Pilgrims’ crossing, a ship guided by an AI captain will embark on the same journey, doing science along the way.
Machine Learning Algorithms Help Scientists Explore Mars
Researchers applied machine learning algorithms to several distinct chemical compositions of Mars and suggest that these algorithms could be a powerful tool to map the planet’s surface on a large scale.
The AI Forecaster: Machine Learning Takes On Weather Prediction
A novel approach to weather forecasting uses convolutional neural networks to generate exceptionally fast global forecasts based on past weather data.
Data from Satellites Help Uncover Exploding Meteors
By using data from two lightning-spotting satellites, researchers measure explosions of thousands of small meteors and create a database that could help the planetary defense community.
Could AI Be Useful for Arctic Communities Facing Sea Ice Loss?
The forecasting tool IceNet promises to be a useful tool for evaluating sea ice loss in the Arctic. But ethical and logistic considerations have to be taken before scientific and Indigenous communities start working together.