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2020 – today
- 2024
[j6]Lukas Gonon, Lyudmila Grigoryeva
, Juan-Pablo Ortega:
Infinite-dimensional reservoir computing. Neural Networks 179: 106486 (2024)- [j5]Francesca Biagini, Lukas Gonon, Niklas Walter:
Approximation Rates for Deep Calibration of (Rough) Stochastic Volatility Models. SIAM J. Financial Math. 15(3): 734-784 (2024) - [c2]Konrad Mueller, Amira Akkari, Lukas Gonon, Ben Wood:
Fast Deep Hedging with Second-Order Optimization. ICAIF 2024: 319-327 - [i23]Francesca Biagini, Lukas Gonon, Niklas Walter:
Universal randomised signatures for generative time series modelling. CoRR abs/2406.10214 (2024) - [i22]Thomas Cass, Lukas Gonon, Nikita Zozoulenko:
Variance Norms for Kernelized Anomaly Detection. CoRR abs/2407.11873 (2024) - [i21]Lukas Gonon, Arnulf Jentzen, Benno Kuckuck, Siyu Liang, Adrian Riekert, Philippe von Wurstemberger:
An Overview on Machine Learning Methods for Partial Differential Equations: from Physics Informed Neural Networks to Deep Operator Learning. CoRR abs/2408.13222 (2024) - [i20]Lukas Gonon, Thilo Meyer-Brandis, Niklas Weber:
Computing Systemic Risk Measures with Graph Neural Networks. CoRR abs/2410.07222 (2024) - [i19]Konrad Mueller, Amira Akkari, Lukas Gonon, Ben Wood:
Fast Deep Hedging with Second-Order Optimization. CoRR abs/2410.22568 (2024) - 2023
- [j4]Lukas Gonon:
Random Feature Neural Networks Learn Black-Scholes Type PDEs Without Curse of Dimensionality. J. Mach. Learn. Res. 24: 189:1-189:51 (2023) - [i18]Lukas Gonon, Robin Graeber, Arnulf Jentzen:
The necessity of depth for artificial neural networks to approximate certain classes of smooth and bounded functions without the curse of dimensionality. CoRR abs/2301.08284 (2023) - [i17]Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega:
Infinite-dimensional reservoir computing. CoRR abs/2304.00490 (2023) - [i16]Lukas Gonon, Antoine Jacquier:
Universal Approximation Theorem and error bounds for quantum neural networks and quantum reservoirs. CoRR abs/2307.12904 (2023) - [i15]Francesca Biagini, Lukas Gonon, Niklas Walter:
Approximation Rates for Deep Calibration of (Rough) Stochastic Volatility Models. CoRR abs/2309.14784 (2023) - 2022
- [j3]Christa Cuchiero, Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega, Josef Teichmann:
Discrete-Time Signatures and Randomness in Reservoir Computing. IEEE Trans. Neural Networks Learn. Syst. 33(11): 6321-6330 (2022) - [i14]Lukas Gonon:
Deep neural network expressivity for optimal stopping problems. CoRR abs/2210.10443 (2022) - [i13]Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega:
Reservoir kernels and Volterra series. CoRR abs/2212.14641 (2022) - 2021
- [j2]Lukas Gonon, Juan-Pablo Ortega:
Fading memory echo state networks are universal. Neural Networks 138: 10-13 (2021) - [i12]Lukas Gonon, Christoph Schwab:
Deep ReLU Network Expression Rates for Option Prices in high-dimensional, exponential Lévy models. CoRR abs/2101.11897 (2021) - [i11]Lukas Gonon, Christoph Schwab:
Deep ReLU Neural Network Approximation for Stochastic Differential Equations with Jumps. CoRR abs/2102.11707 (2021) - [i10]Lukas Gonon:
Random feature neural networks learn Black-Scholes type PDEs without curse of dimensionality. CoRR abs/2106.08900 (2021) - 2020
- [j1]Lukas Gonon, Juan-Pablo Ortega:
Reservoir Computing Universality With Stochastic Inputs. IEEE Trans. Neural Networks Learn. Syst. 31(1): 100-112 (2020) - [i9]Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega:
Approximation Bounds for Random Neural Networks and Reservoir Systems. CoRR abs/2002.05933 (2020) - [i8]Christian Beck, Lukas Gonon, Arnulf Jentzen:
Overcoming the curse of dimensionality in the numerical approximation of high-dimensional semilinear elliptic partial differential equations. CoRR abs/2003.00596 (2020) - [i7]Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega:
Memory and forecasting capacities of nonlinear recurrent networks. CoRR abs/2004.11234 (2020) - [i6]Aritz Bercher, Lukas Gonon, Arnulf Jentzen, Diyora Salimova:
Weak error analysis for stochastic gradient descent optimization algorithms. CoRR abs/2007.02723 (2020) - [i5]Lukas Gonon, Juan-Pablo Ortega:
Fading memory echo state networks are universal. CoRR abs/2010.12047 (2020) - [i4]Christa Cuchiero, Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega, Josef Teichmann:
Discrete-time signatures and randomness in reservoir computing. CoRR abs/2010.14615 (2020)
2010 – 2019
- 2019
- [i3]Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega:
Risk bounds for reservoir computing. CoRR abs/1910.13886 (2019) - [i2]Lukas Gonon, Philipp Grohs, Arnulf Jentzen, David Kofler, David Siska:
Uniform error estimates for artificial neural network approximations for heat equations. CoRR abs/1911.09647 (2019) - 2018
- [i1]Lukas Gonon, Juan-Pablo Ortega:
Reservoir Computing Universality With Stochastic Inputs. CoRR abs/1807.02621 (2018) - 2012
- [c1]Amanda Prorok, Lukas Gonon, Alcherio Martinoli:
Online model estimation of ultra-wideband TDOA measurements for mobile robot localization. ICRA 2012: 807-814
Coauthor Index
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