Patrick Cheridito

37 papers A* 1Journal 36

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Physics-informed diffusion models in spectral space. CoRR Davide Gallon, Philippe von Wurstemberger, Patrick Cheridito, Arnulf Jentzen
2025	J	`jnl`	ABIDES-MARL: A Multi-Agent Reinforcement Learning Environment for Endogenous Price Formation and Execution in a Limit Order Book. CoRR Patrick Cheridito, Jean-Loup Dupret, Zhexin Wu
2025	A*	`conf`	Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows. ICML Gabriele Visentin, Patrick Cheridito
2025	J	`jnl`	Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows. CoRR Gabriele Visentin, Patrick Cheridito
2025	J	`jnl`	Deep Learning for Continuous-time Stochastic Control with Jumps. CoRR Patrick Cheridito, Jean-Loup Dupret, Donatien Hainaut
2025	J	`jnl`	Deep Legendre Transform. CoRR Aleksey Minabutdinov, Patrick Cheridito
2025	J	`jnl`	Robust Optimization in Causal Models and G-Causal Normalizing Flows. CoRR Gabriele Visentin, Patrick Cheridito
2024	J	`jnl`	Gradient Descent Provably Escapes Saddle Points in the Training of Shallow ReLU Networks. J. Optim. Theory Appl. Patrick Cheridito, Arnulf Jentzen, Florian Rossmannek
2023	J	`jnl`	An efficient Monte Carlo scheme for Zakai equations. Commun. Nonlinear Sci. Numer. Simul. Christian Beck, Sebastian Becker, Patrick Cheridito, Arnulf Jentzen, Ariel Neufeld
2023	J	`jnl`	Computation of Conditional Expectations with Guarantees. J. Sci. Comput. Patrick Cheridito, Balint Gersey
2023	J	`jnl`	Efficient Sobolev approximation of linear parabolic PDEs in high dimensions. CoRR Patrick Cheridito, Florian Rossmannek
2022	J	`jnl`	A proof of convergence for gradient descent in the training of artificial neural networks for constant target functions. J. Complex. Patrick Cheridito, Arnulf Jentzen, Adrian Riekert, Florian Rossmannek
2022	J	`jnl`	An efficient Monte Carlo scheme for Zakai equations. CoRR Christian Beck, Sebastian Becker, Patrick Cheridito, Arnulf Jentzen, Ariel Neufeld
2022	J	`jnl`	Efficient Approximation of High-Dimensional Functions With Neural Networks. IEEE Trans. Neural Networks Learn. Syst. Patrick Cheridito, Arnulf Jentzen, Florian Rossmannek
2022	J	`jnl`	Gradient descent provably escapes saddle points in the training of shallow ReLU networks. CoRR Patrick Cheridito, Arnulf Jentzen, Florian Rossmannek
2022	J	`jnl`	Landscape Analysis for Shallow Neural Networks: Complete Classification of Critical Points for Affine Target Functions. J. Nonlinear Sci. Patrick Cheridito, Arnulf Jentzen, Florian Rossmannek
2021	J	`jnl`	A proof of convergence for gradient descent in the training of artificial neural networks for constant target functions. CoRR Patrick Cheridito, Arnulf Jentzen, Adrian Riekert, Florian Rossmannek
2021	J	`jnl`	Computation of conditional expectations with guarantees. CoRR Patrick Cheridito, Balint Gersey
2021	J	`jnl`	Deep Splitting Method for Parabolic PDEs. SIAM J. Sci. Comput. Christian Beck, Sebastian Becker, Patrick Cheridito, Arnulf Jentzen, Ariel Neufeld
2021	J	`jnl`	Deep neural network approximation theory for high-dimensional functions. CoRR Pierfrancesco Beneventano, Patrick Cheridito, Robin Graeber, Arnulf Jentzen, Benno Kuckuck
2021	J	`jnl`	Landscape analysis for shallow ReLU neural networks: complete classification of critical points for affine target functions. CoRR Patrick Cheridito, Arnulf Jentzen, Florian Rossmannek
2021	J	`jnl`	Non-convergence of stochastic gradient descent in the training of deep neural networks. J. Complex. Patrick Cheridito, Arnulf Jentzen, Florian Rossmannek
2020	J	`jnl`	Deep learning based numerical approximation algorithms for stochastic partial differential equations and high-dimensional nonlinear filtering problems. CoRR Christian Beck, Sebastian Becker, Patrick Cheridito, Arnulf Jentzen, Ariel Neufeld
2020	J	`jnl`	High-dimensional approximation spaces of artificial neural networks and applications to partial differential equations. CoRR Pierfrancesco Beneventano, Patrick Cheridito, Arnulf Jentzen, Philippe von Wurstemberger
2020	J	`jnl`	Non-convergence of stochastic gradient descent in the training of deep neural networks. CoRR Patrick Cheridito, Arnulf Jentzen, Florian Rossmannek
2019	J	`jnl`	Deep Optimal Stopping. J. Mach. Learn. Res. Sebastian Becker, Patrick Cheridito, Arnulf Jentzen
2019	J	`jnl`	Deep splitting method for parabolic PDEs. CoRR Christian Beck, Sebastian Becker, Patrick Cheridito, Arnulf Jentzen, Ariel Neufeld
2019	J	`jnl`	Efficient approximation of high-dimensional functions with deep neural networks. CoRR Patrick Cheridito, Arnulf Jentzen, Florian Rossmannek
2019	J	`jnl`	Solving high-dimensional optimal stopping problems using deep learning. CoRR Sebastian Becker, Patrick Cheridito, Arnulf Jentzen, Timo Welti
2017	J	`jnl`	Duality Formulas for Robust Pricing and Hedging in Discrete Time. SIAM J. Financial Math. Patrick Cheridito, Michael Kupper, Ludovic Tangpi
2016	J	`jnl`	Equilibrium Pricing in Incomplete Markets Under Translation Invariant Preferences. Math. Oper. Res. Patrick Cheridito, Ulrich Horst, Michael Kupper, Traian A. Pirvu
2012	J	`jnl`	Pricing and Hedging in Affine Models with Possibility of Default. SIAM J. Financial Math. Patrick Cheridito, Alexander Wugalter
2012	J	`jnl`	Processes of Class Sigma, Last Passage Times, and Drawdowns. SIAM J. Financial Math. Patrick Cheridito, Ashkan Nikeghbali, Eckhard Platen
2006	J	`jnl`	Coherent and convex monetary risk measures for unbounded càdlàg processes. Finance Stochastics Patrick Cheridito, Freddy Delbaen, Michael Kupper
2006	J	`jnl`	Utility maximization under increasing risk aversion in one-period models. Finance Stochastics Patrick Cheridito, Christopher Summer
2005	J	`jnl`	Coherent and convex monetary risk measures for unbounded càdlàg processes. Finance Stochastics Patrick Cheridito, Freddy Delbaen, Michael Kupper
2003	J	`jnl`	Arbitrage in fractional Brownian motion models. Finance Stochastics Patrick Cheridito