5 citations · 5 across the 1 of their papers we have counts for
3 papers
Time Series Viewmakers for Robust Disruption Prediction
Dhruva Chayapathy, Tavis Siebert, Lucas Spangher +3
Machine Learning guided data augmentation may support the development of technologies in the physical sciences, such as nuclear fusion tokamaks. Here we endeavor to study the probl…
Autoregressive Transformers for Disruption Prediction in Nuclear Fusion Plasmas
Lucas Spangher, William Arnold, Alexander Spangher +2
The physical sciences require models tailored to specific nuances of different dynamics. In this work, we study outcome predictions in nuclear fusion tokamaks, where a major challe…
Continuous Convolutional Neural Networks for Disruption Prediction in Nuclear Fusion Plasmas
William F Arnold, Lucas Spangher, Christina Rea
Grid decarbonization for climate change requires dispatchable carbon-free energy like nuclear fusion. The tokamak concept offers a promising path for fusion, but one of the foremos…