A neural network-based approach offers an extremely fast and highly accurate alternative to the "gold standard" of likelihood estimation for statistical modeling of complex datasets.
New paper accepted: Dahal, A., Tanyas, H., van Westen, C., van der Meije, M., Mai, P. M, Huser, R., and Lombardo, L.
Cisneros, D., Richards, J., Dahal, A., Lombardo, L., and Huser, R.
New paper accepted: Gong, Y., Zhong, P., Opitz, T., and Huser, R.
New paper accepted: Huser, R., Stein, M.
KAUST extSTAT Research Group wins prestigious awards at EVA 2023 Conference in Milan.
New paper accepted: Richards, J., Huser, R., Bevacqua, E., and Zscheischler, J.
KAUST graduates are characterized by the rigor of their Ph.D. programs, the long hours spent in the lab and classroom, juggling professional and personal commitments, achieving a work-life balance and, more recently, the ability to adapt to a global pandemic.
