Harnessing Quantitative Finance by Data-Centric Methods
Horvath, B
Pakkannen, M
Muguruza Gonzalez, A
Machine Learning and Data Sciences for Financial Markets, A Guide to Contemporary Practices
(12 May 2023)
https://www.cambridge.org/core/books/abs/machine-learning-and-data-sciences-for-financial-markets/harnessing-quantitative-finance-by-datacentric-methods/64C6AA4497C8BB5B50FCCF4538D32E1F
Sailing in rough waters: examining volatility of fMRI noise
Leppanen, J
Stone, H
Lythgoe, D
Williams, S
Horvath, B
Magnetic Resonance Imaging
volume 78
69-79
(12 Feb 2021)
Deep hedging under rough volatility
Horvath, B
Teichmann, J
Žurič, Ž
Risks
volume 9
issue 7
(20 Jul 2021)
Binary matrix factorisation and completion via integer programming
Gunluk, O
Hauser, R
Kovacs, R
Mathematics of Operations Research
volume 49
issue 2
1278-1302
(04 Aug 2023)
High-performance SVD partial spectrum computation
Keyes, D
Ltaief, H
Nakatsukasa, Y
Sukkari, D
SC '23: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis
(11 Nov 2023)
Predictions for high energy neutrino cross-sections from the ZEUS global PDF fits
Cooper-Sarkar, A
Sarkar, S
(28 Oct 2007)
The high energy neutrino cross-section in the Standard Model and its uncertainty
Cooper-Sarkar, A
Mertsch, P
Sarkar, S
(19 Jun 2011)
Quantifying uncertainties in the high energy neutrino cross-section
Cooper-Sarkar, A
Mertsch, P
Sarkar, S
(08 Aug 2011)
Probing low-x QCD with cosmic neutrinos at the Pierre Auger Observatory
Anchordoqui, L
Cooper-Sarkar, A
Hooper, D
Sarkar, S
(09 May 2006)