Federico Cornalba
6 Publications
2025 | Published | Journal Article | IST-REx-ID: 19027 | 
Cornalba, F., & Fischer, J. L. (2025). Multilevel Monte Carlo methods for the Dean–Kawasaki equation from fluctuating hydrodynamics. SIAM Journal on Numerical Analysis. Society for Industrial and Applied Mathematics. https://doi.org/10.1137/23M1617345
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2024 | Published | Journal Article | IST-REx-ID: 14451 |
Cornalba, F., Disselkamp, C., Scassola, D., & Helf, C. (2024). Multi-objective reward generalization: Improving performance of Deep Reinforcement Learning for applications in single-asset trading. Neural Computing and Applications. Springer Nature. https://doi.org/10.1007/s00521-023-09033-7
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2023 | Published | Journal Article | IST-REx-ID: 14554 |
Cornalba, F., & Shardlow, T. (2023). The regularised inertial Dean’ Kawasaki equation: Discontinuous Galerkin approximation and modelling for low-density regime. ESAIM: Mathematical Modelling and Numerical Analysis. EDP Sciences. https://doi.org/10.1051/m2an/2023077
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2023 | Published | Journal Article | IST-REx-ID: 10551 |
Cornalba, F., & Fischer, J. L. (2023). The Dean-Kawasaki equation and the structure of density fluctuations in systems of diffusing particles. Archive for Rational Mechanics and Analysis. Springer Nature. https://doi.org/10.1007/s00205-023-01903-7
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2021 | Published | Journal Article | IST-REx-ID: 9240 |
Cornalba, F., Shardlow, T., & Zimmer, J. (2021). Well-posedness for a regularised inertial Dean–Kawasaki model for slender particles in several space dimensions. Journal of Differential Equations. Elsevier. https://doi.org/10.1016/j.jde.2021.02.048
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2020 | Published | Journal Article | IST-REx-ID: 7637 |
Cornalba, F., Shardlow, T., & Zimmer, J. (2020). From weakly interacting particles to a regularised Dean-Kawasaki model. Nonlinearity. IOP Publishing. https://doi.org/10.1088/1361-6544/ab5174
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Grants
6 Publications
2025 | Published | Journal Article | IST-REx-ID: 19027 |
Cornalba, F., & Fischer, J. L. (2025). Multilevel Monte Carlo methods for the Dean–Kawasaki equation from fluctuating hydrodynamics. SIAM Journal on Numerical Analysis. Society for Industrial and Applied Mathematics. https://doi.org/10.1137/23M1617345
[Published Version]
View
| Files available
| DOI
| arXiv
2024 | Published | Journal Article | IST-REx-ID: 14451 |
Cornalba, F., Disselkamp, C., Scassola, D., & Helf, C. (2024). Multi-objective reward generalization: Improving performance of Deep Reinforcement Learning for applications in single-asset trading. Neural Computing and Applications. Springer Nature. https://doi.org/10.1007/s00521-023-09033-7
[Published Version]
View
| Files available
| DOI
| PubMed | Europe PMC
| arXiv
2023 | Published | Journal Article | IST-REx-ID: 14554 |
Cornalba, F., & Shardlow, T. (2023). The regularised inertial Dean’ Kawasaki equation: Discontinuous Galerkin approximation and modelling for low-density regime. ESAIM: Mathematical Modelling and Numerical Analysis. EDP Sciences. https://doi.org/10.1051/m2an/2023077
[Published Version]
View
| Files available
| DOI
2023 | Published | Journal Article | IST-REx-ID: 10551 |
Cornalba, F., & Fischer, J. L. (2023). The Dean-Kawasaki equation and the structure of density fluctuations in systems of diffusing particles. Archive for Rational Mechanics and Analysis. Springer Nature. https://doi.org/10.1007/s00205-023-01903-7
[Published Version]
View
| Files available
| DOI
| WoS
| PubMed | Europe PMC
| arXiv
2021 | Published | Journal Article | IST-REx-ID: 9240 |
Cornalba, F., Shardlow, T., & Zimmer, J. (2021). Well-posedness for a regularised inertial Dean–Kawasaki model for slender particles in several space dimensions. Journal of Differential Equations. Elsevier. https://doi.org/10.1016/j.jde.2021.02.048
[Published Version]
View
| Files available
| DOI
| WoS
2020 | Published | Journal Article | IST-REx-ID: 7637 |
Cornalba, F., Shardlow, T., & Zimmer, J. (2020). From weakly interacting particles to a regularised Dean-Kawasaki model. Nonlinearity. IOP Publishing. https://doi.org/10.1088/1361-6544/ab5174
[Preprint]
View
| DOI
| Download Preprint (ext.)
| WoS
| arXiv