activity
20182021
most citedDeep Learning for Plasma Tomography and Disruption Prediction from Bolometer Data

53 citations · 62 across the 3 of their papers we have counts for

collaborators

5 papers

physics.comp-ph20219 cited

Using HPC infrastructures for deep learning applications in fusion research

Diogo R. Ferreira

In the fusion community, the use of high performance computing (HPC) has been mostly dominated by heavy-duty plasma simulations, such as those based on particle-in-cell and gyrokin…

physics.plasm-ph2020

Deep Learning for the Analysis of Disruption Precursors based on Plasma Tomography

Diogo R. Ferreira, Pedro J. Carvalho, Carlo Sozzi +2

The JET baseline scenario is being developed to achieve high fusion performance and sustained fusion power. However, with higher plasma current and higher input power, an increase…

physics.plasm-ph201953 cited

Deep Learning for Plasma Tomography and Disruption Prediction from Bolometer Data

Diogo R. Ferreira, Pedro J. Carvalho, Horácio Fernandes

The use of deep learning is facilitating a wide range of data processing tasks in many areas. The analysis of fusion data is no exception, since there is a need to process large am…

physics.plasm-ph2018

Applications of Deep Learning to Nuclear Fusion Research

Diogo R. Ferreira

Nuclear fusion is the process that powers the sun, and it is one of the best hopes to achieve a virtually unlimited energy source for the future of humanity. However, reproducing s…

physics.comp-ph2018

Full-pulse Tomographic Reconstruction with Deep Neural Networks

Diogo R. Ferreira, Pedro J. Carvalho, Horácio Fernandes

Plasma tomography consists in reconstructing the 2D radiation profile in a poloidal cross-section of a fusion device, based on line-integrated measurements along several lines of s…