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)
Recursive construction of continuum random trees
Rembart, F
Winkel, M
(18 Jul 2016)
A recursive distribution equation for the stable tree
Chee, N
Rembart, F
Winkel, M
(20 Dec 2018)
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)
Continual Learning via Sequential Function-Space Variational Inference
Rudner, T
Smith, F
Feng, Q
Teh, Y
Gal, Y
Proceedings of Machine Learning Research
volume 162
18871-18887
(01 Jan 2022)
Tractable Function-Space Variational Inference in Bayesian Neural Networks
Rudner, T
Chen, Z
Teh, Y
Gal, Y
Advances in Neural Information Processing Systems
volume 35
(01 Jan 2022)