Patrick Cheridito

ETH Zurich — Switzerland

Economics, Econometrics and Finance · Social Sciences

33h-index4.5kcitations111works0.22yr avg
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Research Topics

Stochastic processes and financial applications(65), Risk and Portfolio Optimization(34), Economic theories and models(34), Financial Risk and Volatility Modeling(13), Decision-Making and Behavioral Economics(7)

Publications111 total

Deep Legendre Transform
ArXiv.org·2025Open Access
Deep Legendre Transform
arXiv (Cornell University)·2025Open Access
ABIDES-MARL: A Multi-Agent Reinforcement Learning Environment for Endogenous Price Formation and Execution in a Limit Order Book
arXiv (Cornell University)·2025Open Access
Robust Optimization in Causal Models and G-Causal Normalizing Flows
arXiv (Cornell University)·2025Open Access
Reinforcement Learning for Trade Execution with Market and Limit Orders
arXiv (Cornell University)·2025Open Access
Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows
arXiv (Cornell University)·2025Open Access
Deep Learning for Continuous-Time Stochastic Control with Jumps
arXiv (Cornell University)·2025Open Access
Optimal transport and Wasserstein distances for causal models
Bernoulli·2025· 1 cited
Gradient Descent Provably Escapes Saddle Points in the Training of Shallow ReLU Networks
Journal of Optimization Theory and Applications·2024· 1 citedOpen Access
An efficient Monte Carlo scheme for Zakai equations
Communications in Nonlinear Science and Numerical Simulation·2023· 1 citedOpen Access
Efficient Sobolev approximation of linear parabolic PDEs in high dimensions
arXiv (Cornell University)·2023Open Access
Optimal transport and Wasserstein distances for causal models
arXiv (Cornell University)·2023Open Access
Computation of Conditional Expectations with Guarantees
Journal of Scientific Computing·2023· 1 citedOpen Access
An efficient Monte Carlo scheme for Zakai equations
arXiv (Cornell University)·2022Open Access
Gradient descent provably escapes saddle points in the training of shallow ReLU networks
arXiv (Cornell University)·2022· 1 citedOpen Access
Landscape Analysis for Shallow Neural Networks: Complete Classification of Critical Points for Affine Target Functions
Journal of Nonlinear Science·2022· 10 citedOpen Access
A proof of convergence for gradient descent in the training of artificial neural networks for constant target functions
Journal of Complexity·2022· 24 citedOpen Access
Deep neural network approximation theory for high-dimensional functions
arXiv (Cornell University)·2021· 4 citedOpen Access
Non-convergence of stochastic gradient descent in the training of deep neural networks
Repository for Publications and Research Data (ETH Zurich)·2021· 37 citedOpen Access
Landscape analysis for shallow ReLU neural networks: complete classification of critical points for affine target functions.
arXiv (Cornell University)·2021· 11 citedOpen Access
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Frequent Co-authors

Michael Kupper(13), Arnulf Jentzen(7), Freddy Delbaen(5), Damir Filipović(5), Florian Rossmannek(5), Robert L. Kimmel(4), Kihun Nam(3), H. Meté Soner(2), Nizar Touzi(2), Tianhui Li(2), S. Becker(2), Mitja Stadje(2), Ludovic Tangpi(2), Markus K. Brunnermeier(2), Ulrich Horst(2), Traian A. Pirvu(2), Zhikai Xu(2), Hideyuki Kawaguchi(1), Makoto Maejima(1), Nicolas Victoir(1)