A. Ho

Zanisi, L. ., Ho, A. ., Barr, J. ., Madula, T. ., Citrin, J. ., Pamela, S. ., … Gopakumar, V. . (2024). Efficient training sets for surrogate models of tokamak turbulence with Active Deep Ensembles. Nuclear Fusion, 64(3), 036022. https://doi.org/10.1088/1741-4326/ad240d

Fransson, E. ., Gillgren, A. ., Ho, A. ., Borsander, J. ., Lindberg, O. ., Rieck, W. ., … Strand, P. . (2023). A fast neural network surrogate model for the eigenvalues of QuaLiKiz. Physics of Plasmas, 30(12), 123904. https://doi.org/10.1063/5.0174643

Solano, E. ., Birkenmeier, G. ., Silva, C. ., Delabie, E. ., Hillesheim, J. ., Baciero, A. ., … Contributors, J. . (2023). L-H transition studies in tritium and deuterium–tritium campaigns at JET with Be wall and W divertor. Nuclear Fusion, 63(11), 112011. https://doi.org/10.1088/1741-4326/acee12

Garcia, J. ., Casson, F. ., Frassinetti, L. ., Gallart, D. ., Garzotti, L. ., Kim, H. ., … Contributors, J. . (2023). Modelling performed for predictions of fusion power in JET DTE2: overview and lessons learnt. Nuclear Fusion, 63(11), 112003. https://doi.org/10.1088/1741-4326/acedc0

Kim, H. ., Auriemma, F. ., Ferreira, J. ., Gabriellini, S. ., Ho, A. ., Huynh, P. ., … Contributors, J. . (2023). Validation of D-T fusion power prediction capability against 2021 JET D-T experiments. Nuclear Fusion, 63(11), 112004. https://doi.org/10.1088/1741-4326/ace26d

Hobirk, J. ., Challis, C. ., Kappatou, A. ., Lerche, E. ., Keeling, D. ., King, D. ., … Contributors, J. . (2023). The JET hybrid scenario in Deuterium, Tritium and Deuterium-Tritium. Nuclear Fusion, 63(11), 112001. https://doi.org/10.1088/1741-4326/acde8d

Bosman, T. ., Kochl, F. ., Ho, A. ., de Baar, M. ., Krishnamoorthy, D. ., & van Berkel, M. . (2023). Integrated model control simulations of the electron density profile and the implications of using multiple hybrid pellet injectors for control. Nuclear Fusion, 63(12), 126047. https://doi.org/10.1088/1741-4326/ad0251

Kremers, B. J., Citrin, J. ., Ho, A. ., & van de Plassche, K. . (2023). Two-step clustering for data reduction combining DBSCAN and k-means clustering. Contributions to Plasma Physics, 63(5-6), 202200177. https://doi.org/10.1002/ctpp.202200177

Marin, M. ., Citrin, J. ., Giroud, C. ., Bourdelle, C. ., Camenen, Y. ., Garzotti, L. ., … Contributors, J. . (2023). Integrated modelling of Neon impact on JET H-mode core plasmas. Nuclear Fusion, 63(1), 016019. https://doi.org/10.1088/1741-4326/aca469

Ho, A. ., Citrin, J. ., Challis, C. D., Bourdelle, C. ., Casson, F. J., Garcia, J. ., … Mailloux, J. . (2023). Predictive JET current ramp-up modelling using QuaLiKiz-neural-network. Nuclear Fusion, 63(6), 066014. https://doi.org/10.1088/1741-4326/acc083