ORNL researchers turn to deep learning to solve science's big data problem

IMAGE: Scientists will use ORNL's computing resources such as the Titan supercomputer to develop deep learning solutions for data analysis. A team of researchers from Oak Ridge National Lab oratory has been awarded nearly $2 million over three years from the Department of Energy to explore the potential of machine learning in revolutionizing scientific data analysis. The Advances in Machine Learning to Improve Scientific Discovery at Exascale and Beyond (ASCEND) project aims to use deep learning to assist researchers in making sense of massive datasets produced at the world's most sophisticated scientific facilities. Deep learning is an area of machine learning that uses artificial neural networks to enable self-learning devices and platforms. The team, led by ORNL's Thomas Potok, includes Robert Patton, Chris Symons, Steven Young and Catherine Schuman.