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Anzahl der Publikationen: 25

Zeitschriftenartikel

Biagini, Francesca ORCID logoORCID: https://orcid.org/0000-0001-9801-5259; Gonon, Lukas ORCID logoORCID: https://orcid.org/0000-0003-3367-2455; Mazzon, Andrea und Meyer-Brandis, Thilo ORCID logoORCID: https://orcid.org/0000-0002-6374-7983 (Januar 2025): Detecting asset price bubbles using deep learning. In: Mathematical Finance, Bd. 35, Nr. 1: S. 74-110

Biagini, Francesca ORCID logoORCID: https://orcid.org/0000-0001-9801-5259; Gonon, Lukas und Walter, Niklas (2024): Approximation Rates for Deep Calibration of (Rough) Stochastic Volatility Models. In: SIAM Journal on Financial Mathematics, Bd. 15, Nr. 3: S. 734-784

Gonon, Lukas; Grigoryeva, Lyudmila und Ortega, Juan-Pablo (2023): Approximation bounds for random neural networks and reservoir systems. In: Annals of Applied Probability, Bd. 33, Nr. 1: S. 28-69

Gonon, Lukas ORCID logoORCID: https://orcid.org/0000-0003-3367-2455 (2023): Random Feature Neural Networks Learn Black-Scholes Type PDEs Without Curse of Dimensionality. In: Journal of Machine Learning Research, Bd. 24, Nr. 189: S. 8965-9015

Gonon, Lukas und Schwab, Christoph (2023): Deep ReLU neural networks overcome the curse of dimensionality for partial integrodifferential equations. In: Analysis and Applications, Bd. 21, Nr. 01: S. 1-47

Gonon, Lukas und Schwab, Christoph (2022): Deep ReLU neural networks overcome the curse of dimensionality for partial integrodifferential equations. In: Analysis and Applications, Bd. 21, Nr. 1: S. 1-47

Cuchiero, Christa; Gonon, Lukas; Grigoryeva, Lyudmila; Ortega, Juan-Pablo und Teichmann, Josef (2022): Discrete-Time Signatures and Randomness in Reservoir Computing. In: IEEE Transactions on Neural Networks and Learning Systems, Bd. 33, Nr. 11: S. 6321-6330

Biagini, Francesca ORCID logoORCID: https://orcid.org/0000-0001-9801-5259; Gonon, Lukas und Reitsam, Thomas (2022): Neural network approximation for superhedging prices. In: Mathematical Finance, Bd. 33, Nr. 1: S. 146-184 [PDF, 1MB]

Cuchiero, Christa; Gonon, Lukas ORCID logoORCID: https://orcid.org/0000-0003-3367-2455; Grigoryeva, Lyudmila; Ortega, Juan-Pablo ORCID logoORCID: https://orcid.org/0000-0002-5412-9622 und Teichmann, Josef (2022): Discrete-Time Signatures and Randomness in Reservoir Computing. In: IEEE Transactions on Neural Networks and Learning Systems, Bd. 33, Nr. 11: S. 6321-6330

Gonon, Lukas ORCID logoORCID: https://orcid.org/0000-0003-3367-2455 und Schwab, Christoph (2021): Deep ReLU network expression rates for option prices in high-dimensional, exponential Lévy models. In: Finance and Stochastics, Bd. 25: S. 615-657 [PDF, 1MB]

Gonon, Lukas; Grohs, Philipp; Jentzen, Arnulf; Kofler, David und Šiška, David (2021): Uniform error estimates for artificial neural network approximations for heat equations. In: IMA Journal of Numerical Analysis, Bd. 42, Nr. 3: S. 1991-2054

Beck, Christian; Gonon, Lukas ORCID logoORCID: https://orcid.org/0000-0003-3367-2455; Hutzenthaler, Martin und Jentzen, Arnulf (2021): On existence and uniqueness properties for solutions of stochastic fixed point equations. In: Discrete and Continuous Dynamical Systems-Series B, Bd. 26, Nr. 9: S. 4927-4962

Gonon, Lukas ORCID logoORCID: https://orcid.org/0000-0003-3367-2455; Muhle-Karbe, Johannes und Shi, Xiaofei (2021): Asset pricing with general transaction costs: Theory and numerics. In: Mathematical Finance, Bd. 31, Nr. 2: S. 595-648

Gonon, Lukas ORCID logoORCID: https://orcid.org/0000-0003-3367-2455 und Ortega, Juan-Pablo (2021): Fading memory echo state networks are universal. In: Neural Networks, Bd. 138: S. 10-13

Gonon, Lukas ORCID logoORCID: https://orcid.org/0000-0003-3367-2455; Grigoryeva, Lyudmila und Ortega, Juan-Pablo (2020): Risk Bounds for Reservoir Computing. In: Journal of Machine Learning Research, Bd. 21, 240

Gonon, Lukas ORCID logoORCID: https://orcid.org/0000-0003-3367-2455 und Ortega, Juan-Pablo ORCID logoORCID: https://orcid.org/0000-0002-5412-9622 (2020): Reservoir Computing Universality With Stochastic Inputs. In: IEEE Transactions on Neural Networks and Learning Systems, Bd. 31, Nr. 1: S. 100-112

Gonon, Lukas ORCID logoORCID: https://orcid.org/0000-0003-3367-2455 und Teichmann, Josef (2020): Linearized filtering of affine processes using stochastic Riccati equations. In: Stochastic Processes and their Applications, Bd. 130, Nr. 1: S. 394-430

Gonon, Lukas ORCID logoORCID: https://orcid.org/0000-0003-3367-2455; Grigoryeva, Lyudmila und Ortega, Juan-Pablo (2020): Memory and forecasting capacities of nonlinear recurrent networks. In: Physica D-Nonlinear Phenomena, Bd. 414, 132721

Buehler, H.; Gonon, Lukas ORCID logoORCID: https://orcid.org/0000-0003-3367-2455; Teichmann, J. und Wood, B. (2019): Deep hedging. In: Quantitative Finance, Bd. 19, Nr. 8: S. 1271-1291

Döring, Leif; Gonon, Lukas; Prömel, David J. ORCID logoORCID: https://orcid.org/0000-0001-7028-7500 und Reichmann, Oleg (2019): Existence and Uniqueness Results for Time-Inhomogeneous Time-Change Equations and Fokker–Planck Equations. In: Journal of Theoretical Probability, Bd. 34, Nr. 1: S. 173-205

Döring, Leif; Gonon, Lukas; Prömel, David J. und Reichmann, Oleg (2019): On Skorokhod embeddings and Poisson equations. In: Annals of Applied Probability, Bd. 29, Nr. 4

Gonon, Lukas und Rogers, L. C. G. (2014): Evolution of Firm Size. In: International Journal of Theoretical and Applied Finance, Bd. 17, Nr. 05, 1450031

Paper

Gonon, Lukas ORCID logoORCID: https://orcid.org/0000-0003-3367-2455; Meyer-Brandis, Thilo ORCID logoORCID: https://orcid.org/0000-0002-6374-7983 und Weber, Niklas (30. September 2024): Computing Systemic Risk Measures with Graph Neural Networks.

Biagini, Francesca ORCID logoORCID: https://orcid.org/0000-0001-9801-5259; Gonon, Lukas ORCID logoORCID: https://orcid.org/0000-0003-3367-2455 und Walter, Niklas (14. Juni 2024): Universal randomised signatures for generative time series modelling. [PDF, 653kB]

Konferenzbeitrag

Prorok, Amanda; Gonon, Lukas ORCID logoORCID: https://orcid.org/0000-0003-3367-2455 und Martinoli, Alcherio (2012): Online model estimation of ultra-wideband TDOA measurements for mobile robot localization. 2012 IEEE International Conference on Robotics and Automation, Saint Paul, USA, 14. - 18. Mai 2012. In: 2012 IEEE International Conference on Robotics and Automation, Piscataway, NJ, USA: IEEE. S. 807-814

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