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ORCIDFederico Cornalba
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2020 – today
- 2024
[j2]Federico Cornalba
, Constantin Disselkamp, Davide Scassola, Christopher Helf:
Multi-objective reward generalization: improving performance of Deep Reinforcement Learning for applications in single-asset trading. Neural Comput. Appl. 36(2): 619-637 (2024)- [i7]Sebastian Zimper, Federico Cornalba, Natasa Djurdjevac Conrad, Ana Djurdjevac:
On reduced inertial PDE models for Cucker-Smale flocking dynamics. CoRR abs/2407.18717 (2024) - [i6]Ivan Cheltsov, Federico Cornalba, Clarice Poon, Tony Shardlow:
Hadamard Langevin dynamics for sampling sparse priors. CoRR abs/2411.11403 (2024) - 2023
- [i5]Federico Cornalba, Julian Fischer, Jonas Ingmanns, Claudia Raithel:
Density fluctuations in weakly interacting particle systems via the Dean-Kawasaki equation. CoRR abs/2303.00429 (2023) - [i4]Federico Cornalba, Julian Fischer:
Multilevel Monte Carlo methods for the Dean-Kawasaki equation from Fluctuating Hydrodynamics. CoRR abs/2311.08872 (2023) - 2022
- [i3]Federico Cornalba, Constantin Disselkamp, Davide Scassola, Christopher Helf:
Multi-Objective reward generalization: Improving performance of Deep Reinforcement Learning for selected applications in stock and cryptocurrency trading. CoRR abs/2203.04579 (2022) - [i2]Federico Cornalba, Tony Shardlow:
The Regularised Inertial Dean-Kawasaki equation: discontinuous Galerkin approximation and modelling for low-density regime. CoRR abs/2207.09989 (2022) - 2021
- [i1]Federico Cornalba, Julian Fischer:
The Dean-Kawasaki equation and the structure of density fluctuations in systems of diffusing particles. CoRR abs/2109.06500 (2021)
2010 – 2019
- 2019
- [j1]Federico Cornalba, Tony Shardlow, Johannes Zimmer:
A Regularized Dean-Kawasaki Model: Derivation and Analysis. SIAM J. Math. Anal. 51(2): 1137-1187 (2019)
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