Research output per year
Research output per year
Personal profile
Research profile
His recent research has been focused on developing machine learning techniques in computational finance. His work won "Risks 2020 Best Paper Award" (journal), "Best Presentation Award" (international conference).
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Collaborations and top research areas from the last five years
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Monte Carlo simulation of SDEs using GANs
van Rhijn, J., Oosterlee, C. W., Grzelak, L. A. & Liu, S., 2022, In: JAPAN JOURNAL OF INDUSTRIAL AND APPLIED MATHEMATICS. 40 (2023), 3, p. 1359-1390 32 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open AccessFile1 Citation (Scopus)31 Downloads (Pure) -
On a Neural Network to Extract Implied Information from American Options
Liu, S., Leitao Rodriguez, A., Borovykh, A. & Oosterlee, C. W., 2022, In: Applied Mathematical Finance. 28, 5, p. 449-475 27 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open AccessFile4 Citations (Scopus)39 Downloads (Pure) -
The Seven-League Scheme: Deep Learning for Large Time Step Monte Carlo Simulations of Stochastic Differential Equations
Liu, S., Grzelak, L. A. & Oosterlee, C. W., 2022, In: Risks. 10, 3, 27 p., 47.Research output: Contribution to journal › Article › Scientific › peer-review
Open AccessFile5 Citations (Scopus)95 Downloads (Pure) -
Supervised deep learning in computational finance
Liu, S., 2021, 160 p.Research output: Thesis › Dissertation (TU Delft)
Open AccessFile461 Downloads (Pure) -
A neural network-based framework for financial model calibration
Liu, S., Borovykh, A., Grzelak, L. & Oosterlee, C. W., 2019, In: Mathematics in Industry. 9, 1, p. 1-28 28 p., 9.Research output: Contribution to journal › Article › Scientific › peer-review
Open AccessFile59 Citations (Scopus)297 Downloads (Pure)