| Machine learning in finance MF Dixon, I Halperin, P Bilokon Springer International Publishing, 2020 | 305 | 2020 |
| Machine learning in finance (Vol. 1170) MF Dixon, I Halperin, P Bilokon Springer International Publishing 10, 978-3, 2020 | 47 | 2020 |
| Machine Learning and Big Data with kdb+/q J Novotny, PA Bilokon, A Galiotos, F Délèze John Wiley & Sons, 2019 | 11 | 2019 |
| A domain-theoretic approach to Brownian motion and general continuous stochastic processes P Bilokon, A Edalat Proceedings of the Joint Meeting of the Twenty-Third EACSL Annual Conference …, 2014 | 9 | 2014 |
| Applications of reinforcement learning MF Dixon, I Halperin, P Bilokon, MF Dixon, I Halperin, P Bilokon Machine Learning in Finance: From Theory to Practice, 347-418, 2020 | 7 | 2020 |
| Feedforward Neural Networks MF Dixon, I Halperin, P Bilokon, MF Dixon, I Halperin, P Bilokon Machine Learning in Finance: From Theory to Practice, 111-166, 2020 | 7 | 2020 |
| Numerical Solutions of Differential Equations S Amen, P Bilokon, A Brinley-Codd, M Fofaria, T Shah Imperial College London, 2004 | 7 | 2004 |
| Transformers versus LSTMs for electronic trading P Bilokon, Y Qiu arXiv preprint arXiv:2309.11400, 2023 | 5 | 2023 |
| Benchmarking specialized databases for high-frequency data F Barez, P Bilokon, R Xiong arXiv preprint arXiv:2301.12561, 2023 | 4 | 2023 |
| Exploring the advantages of transformers for high-frequency trading F Barez, P Bilokon, A Gervais, N Lisitsyn arXiv preprint arXiv:2302.13850, 2023 | 3 | 2023 |
| Machine Learning and Big Data with KDB+/Q: Q, High Frequency Financial Data and Algorithmic Trading PA Bilokon, J Novotny John Wiley & Sons, Incorporated, 2019 | 3 | 2019 |
| Market regime classification with signatures P Bilokon, A Jacquier, C McIndoe arXiv preprint arXiv:2107.00066, 2021 | 2 | 2021 |
| Inverse reinforcement learning and imitation learning MF Dixon, I Halperin, P Bilokon, MF Dixon, I Halperin, P Bilokon Machine Learning in Finance: From Theory to Practice, 419-517, 2020 | 2 | 2020 |
| From Deep Filtering to Deep Econometrics R Stok, P Bilokon arXiv preprint arXiv:2311.06256, 2023 | 1 | 2023 |
| Quasi-Monte Carlo Methods for Calculating Derivatives Sensitivities on the GPU S Kucherenko, P Bilokon, C Williams Wilmott 127, 2023, 2023 | 1 | 2023 |
| Iterated and exponentially weighted moving principal component analysis P Bilokon, D Finkelstein arXiv preprint arXiv:2108.13072, 2021 | 1 | 2021 |
| Identification and validation of Triamcinolone and Gallopamil as treatments for early COVID-19 via an in silico repurposing pipeline M MacMahon, W Hwang, S Yim, E MacMahon, A Abraham, J Barton, ... | 1 | 2021 |
| Frontiers of machine learning and finance MF Dixon, I Halperin, P Bilokon, MF Dixon, I Halperin, P Bilokon Machine learning in finance: From theory to practice, 519-541, 2020 | 1 | 2020 |
| From Deep Learning to Deep Econometrics R Stok, P Bilokon, J Simonian The Journal of Financial Data Science, 2024 | | 2024 |
| Evolution-Bootstrapped Simulation: Artificial or Human Intelligence: Which Came First? PA Bilokon arXiv preprint arXiv:2402.00030, 2024 | | 2024 |
Igor HalperinFidelityVerified email at fmr.com
