CANDLE-UNO
CANDLE (Exascale Deep Learning and Simulation Enabled Precision Medicine for Cancer) project aims to implement deep learning architectures that are relevant to problems in cancer.
Benchmarks
A list of benchmarks we currently work on
Currently we are working on a number of sientific applications.
Benchmark Science Task Owner Institute Specific Benchmark Targets
CloudMask Climate Segmentation RAL link cloudmask specifics STEMDL Material Classification ORNL link stemdl specifics CANDLE-UNO Medicine Classification ANL link candle-uno specifics TEvolOp Forecasting Earthquake Regression University of Virginia link tevolop specifics
CloudMask (Segmentation)
Estimation of sea surface temperature (SST) from space-borne sensors.
TEvolOp Earthquake Forecasting
Forcasting Earthquakes
STEMDL (Classification)
State of the art scanning transmission electron microscopes (STEM) produce focused electron beams with atomic dimensions and allow to capture diffraction patterns arising from the interaction of incident electrons with nanoscale material volumes.