A. Ho

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., … JET Contributors,. (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

Mailloux, J., Abid, N., Abraham, K., Abreu, P., Adabonyan, O., Citrin, J., … Zychor, I. (2022). Overview of JET results for optimising ITER operation. Nuclear Fusion, 62(4), 042026. https://doi.org/10.1088/1741-4326/ac47b4

Ho, A., Citrin, J., Bourdelle, C., Camenen, Y., Casson, F., van de Plassche, K., … JET Contributors,. (2021). Neural network surrogate of QuaLiKiz using JET experimental data to populate training space. Physics of Plasmas, 28(3), 032305. https://doi.org/10.1063/5.0038290

Marin, M., Citrin, J., Garzotti, L., Valovic, M., Bourdelle, C., Camenen, Y., … JET Contributors,. (2021). Multiple-isotope pellet cycles captured by turbulent transport modelling in the JET tokamak. Nuclear Fusion, 61(3), 036042. https://doi.org/10.1088/1741-4326/abda00

Ho, A. (2021). Development of neural networks towards predict-first plasma modelling (Eindhoven University of Technology). Eindhoven University of Technology, Eindhoven, Netherlands. Retrieved from https://research.tue.nl/en/publications/development-of-neural-networks-towards-predict-first-plasma-model (Original work published)

Van Mulders, S., Felici, F., Sauter, O., Citrin, J., Ho, A., Marin, M., & van de Plassche, K. (2021). Rapid optimization of stationary tokamak plasmas in RAPTOR: demonstration for the ITER hybrid scenario with neural network surrogate transport model QLKNN. Nuclear Fusion, 61(8), 086019. https://doi.org/10.1088/1741-4326/ac0d12

van de Plassche, K. L., Citrin, J., Bourdelle, C., Camenen, Y., Casson, F. J., Dagnelie, V. I., … Van Mulders, S. (2020). Fast modelling of turbulent transport in fusion plasmas using neural networks. Physics of Plasmas, 27(2), 022310. https://doi.org/10.1063/1.5134126

Marin, M., Citrin, J., Bourdelle, C., Camenen, Y., Casson, F. J., Ho, A., … JET Contributors,. (2020). First-principles-based multiple-isotope particle transport modelling at JET. Nuclear Fusion, 60(4), 046007. https://doi.org/10.1088/1741-4326/ab60d1