Artificial Intelligence Projects

Deep learning has enabled state-of-the-art results in high-energy neutrino physics. This application achieves 5x better background particle rejection compared to classical techniques.

Argonne is working to enhance the reliability of AI techniques applied to experimental data for the NEXT experiment.

Argonne’s novel AI algorithm drastically reduces design optimization times and costs compared with current state-of-the-art techniques.

Argonne is using artificial intelligence to enable accelerated simulation-driven design and optimization of jet engine cooling schemes.

Argonne is improving deep learning algorithms to detect wildfires earlier, saving lives and ecosystems.

Argonne is using vision transformers to build highly accurate medium-range weather forecasting models. They run at a fraction of the cost of traditional Numerical Weather Prediction and will help the energy industry respond to weather extremes.

For some lattice QCD distributions, models trained at Argonne outperform traditional state-of-the-art algorithms.

Argonne is employing deep neural networks to replace computationally expensive parameterizations of certain physical schemes in the Weather Research and Forecasting model.

Argonne’s innovative tools combine machine learning with advanced spectral analysis to elucidate structure in quantum materials.

MLExchange is a software framework designed to facilitate collaboration among researchers, provide ML solutions, and reduce the barriers to use ML tools.