DOE Science Showcase - Deep Learning Neural Networks
Research Scientific Computing Center (NERSC) has implemented
a deep learning data pipeline for the Daya Bay experiment.
Image Credit: Lawrence Berkeley National Laboratory
Deep learning neural networks are based on a class of machine algorithms that can learn to find patterns and closely represent those patterns at many levels. As additional information is received, the network refines those patterns, gains experience, and improves its probabilities, essentially learning from past mistakes. This is called “deep learning” because the networks that are involved have a depth of more than just a few layers.
Basic deep learning concepts were developed many years ago; with today’s availability of high performance computing environments and massive datasets, there has been a resurgence of deep learning neural network research throughout the science community. Scalable tools are being developed to train these networks, and brain-inspired computing algorithms are achieving state-of-the-art results on tasks such as visual object classification, speech and image recognition, bioinfomatics, particle physics, neuroscience, language modeling, and natural language understanding. More information, including DOE research reports, publications, and data collections about deep learning networks, is available in the DOE databases and related resources provided below.
Related Research Information in DOE Databases
- DOE PAGES – journal articles and accepted manuscripts related to deep learning research.
- SciTech Connect – deep learning research from DOE science, technology, and engineering programs.
- In the OSTI Collections – Deep Learning, Dr. William Watson, OSTI
For additional information, see the OSTI Catalogue of Collections.
- Deep Learning, Wikipedia
- Machine Learning, Wikipedia
- Artificial Neural Network, Wikipedia
- Speech Recognition, Wikipedia
- DOE Office of Science
- National Nuclear Security Administration
- Lawrence Berkeley National Laboratory (LBNL)
- Berkeley Lab Explores Frontiers of Deep Learning for Science, LBNL
- National Energy Research Scientific Computing Center (NERSC), LBNL
- Lawrence Livermore National Laboratory (LLNL)
- Advanced Simulation and Computing, LLNL
- LLNL Partners with IBM on Brain-Like Computing Chip, ScienceCinema
- TrueNorth Ecosystem for Brain-Inspired Computing: Scalable Systems, Software, and Applications, SciTech Connect
- The Livermore Brain: Massive Deep Learning Networks Enabled by High Performance Computing, SciTech Connect
- Taking Aim at Cancer, Innovation
- Argonne National Laboratory (ANL)
- Two Argonne-led projects among $39.8 million in first-round Exascale Computing Project awards, ANL
- U.S. Air Force Research Laboratory
- U.S. Army Research Laboratory
- Deep Learning Will Radically Change the Ways We Interact with Technology, Aditya Singh, Harvard Business Review