Lukas Gonon - RankMe

40 papers A* 3Journal 35Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Distributional Adversarial Attacks and Training in Deep Hedging. CoRR Guangyi He, Tobias Sutter, Lukas Gonon
2025	J	`jnl`	Error analysis for the deep Kolmogorov method. CoRR Iulian Cîmpean, Thang Do, Lukas Gonon, Arnulf Jentzen, Ionel Popescu
2025	J	`jnl`	Feedback-driven recurrent quantum neural network universality. CoRR Lukas Gonon, Rodrigo Martínez-Peña, Juan-Pablo Ortega
2025	J	`jnl`	Infinite-dimensional Mahalanobis Distance with Applications to Kernelized Novelty Detection. J. Mach. Learn. Res. Nikita Zozoulenko, Thomas Cass, Lukas Gonon
2025	—	`conf`	Leveraging Deep Learning Optimization for Monte Carlo Calibration of (Rough) Stochastic Volatility Models. ICAIF Lukas Gonon, Wolfgang Stockinger
2025	A*	`conf`	Operator Deep Smoothing for Implied Volatility. ICLR Ruben Wiedemann, Antoine Jacquier, Lukas Gonon
2025	A*	`conf`	Random Feature Representation Boosting. ICML Nikita Zozoulenko, Thomas Cass, Lukas Gonon
2025	J	`jnl`	Random Feature Representation Boosting. CoRR Nikita Zozoulenko, Thomas Cass, Lukas Gonon
2025	J	`jnl`	Universal Approximation Theorem and Error Bounds for Quantum Neural Networks and Quantum Reservoirs. IEEE Trans. Neural Networks Learn. Syst. Lukas Gonon, Antoine Jacquier
2024	J	`jnl`	An Overview on Machine Learning Methods for Partial Differential Equations: from Physics Informed Neural Networks to Deep Operator Learning. CoRR Lukas Gonon, Arnulf Jentzen, Benno Kuckuck, Siyu Liang, Adrian Riekert, Philippe von Wurstemberger
2024	J	`jnl`	Approximation Rates for Deep Calibration of (Rough) Stochastic Volatility Models. SIAM J. Financial Math. Francesca Biagini, Lukas Gonon, Niklas Walter
2024	J	`jnl`	Computing Systemic Risk Measures with Graph Neural Networks. CoRR Lukas Gonon, Thilo Meyer-Brandis, Niklas Weber
2024	—	`conf`	Fast Deep Hedging with Second-Order Optimization. ICAIF Konrad Mueller, Amira Akkari, Lukas Gonon, Ben Wood
2024	J	`jnl`	Fast Deep Hedging with Second-Order Optimization. CoRR Konrad Mueller, Amira Akkari, Lukas Gonon, Ben Wood
2024	J	`jnl`	Infinite-dimensional reservoir computing. Neural Networks Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega
2024	J	`jnl`	Universal randomised signatures for generative time series modelling. CoRR Francesca Biagini, Lukas Gonon, Niklas Walter
2024	J	`jnl`	Variance Norms for Kernelized Anomaly Detection. CoRR Thomas Cass, Lukas Gonon, Nikita Zozoulenko
2023	J	`jnl`	Approximation Rates for Deep Calibration of (Rough) Stochastic Volatility Models. CoRR Francesca Biagini, Lukas Gonon, Niklas Walter
2023	J	`jnl`	Infinite-dimensional reservoir computing. CoRR Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega
2023	J	`jnl`	Random Feature Neural Networks Learn Black-Scholes Type PDEs Without Curse of Dimensionality. J. Mach. Learn. Res. Lukas Gonon
2023	J	`jnl`	The necessity of depth for artificial neural networks to approximate certain classes of smooth and bounded functions without the curse of dimensionality. CoRR Lukas Gonon, Robin Graeber, Arnulf Jentzen
2023	J	`jnl`	Universal Approximation Theorem and error bounds for quantum neural networks and quantum reservoirs. CoRR Lukas Gonon, Antoine Jacquier
2022	J	`jnl`	Deep neural network expressivity for optimal stopping problems. CoRR Lukas Gonon
2022	J	`jnl`	Discrete-Time Signatures and Randomness in Reservoir Computing. IEEE Trans. Neural Networks Learn. Syst. Christa Cuchiero, Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega, Josef Teichmann
2022	J	`jnl`	Reservoir kernels and Volterra series. CoRR Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega
2021	J	`jnl`	Deep ReLU Network Expression Rates for Option Prices in high-dimensional, exponential Lévy models. CoRR Lukas Gonon, Christoph Schwab
2021	J	`jnl`	Deep ReLU Neural Network Approximation for Stochastic Differential Equations with Jumps. CoRR Lukas Gonon, Christoph Schwab
2021	J	`jnl`	Fading memory echo state networks are universal. Neural Networks Lukas Gonon, Juan-Pablo Ortega
2021	J	`jnl`	Random feature neural networks learn Black-Scholes type PDEs without curse of dimensionality. CoRR Lukas Gonon
2020	J	`jnl`	Approximation Bounds for Random Neural Networks and Reservoir Systems. CoRR Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega
2020	J	`jnl`	Discrete-time signatures and randomness in reservoir computing. CoRR Christa Cuchiero, Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega, Josef Teichmann
2020	J	`jnl`	Fading memory echo state networks are universal. CoRR Lukas Gonon, Juan-Pablo Ortega
2020	J	`jnl`	Memory and forecasting capacities of nonlinear recurrent networks. CoRR Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega
2020	J	`jnl`	Overcoming the curse of dimensionality in the numerical approximation of high-dimensional semilinear elliptic partial differential equations. CoRR Christian Beck, Lukas Gonon, Arnulf Jentzen
2020	J	`jnl`	Reservoir Computing Universality With Stochastic Inputs. IEEE Trans. Neural Networks Learn. Syst. Lukas Gonon, Juan-Pablo Ortega
2020	J	`jnl`	Weak error analysis for stochastic gradient descent optimization algorithms. CoRR Aritz Bercher, Lukas Gonon, Arnulf Jentzen, Diyora Salimova
2019	J	`jnl`	Risk bounds for reservoir computing. CoRR Lukas Gonon, Lyudmila Grigoryeva, Juan-Pablo Ortega
2019	J	`jnl`	Uniform error estimates for artificial neural network approximations for heat equations. CoRR Lukas Gonon, Philipp Grohs, Arnulf Jentzen, David Kofler, David Siska
2018	J	`jnl`	Reservoir Computing Universality With Stochastic Inputs. CoRR Lukas Gonon, Juan-Pablo Ortega
2012	A*	`conf`	Online model estimation of ultra-wideband TDOA measurements for mobile robot localization. ICRA Amanda Prorok, Lukas Gonon, Alcherio Martinoli