Backward Stochastic Difference Equations and Nearly Time-Consistent Nonlinear Expectations. - Samuel N. Cohen; Robert J. Elliott (SIAM J. Control. Optim., 2011)

Ergodic BSDEs Driven by Markov Chains. - Samuel N. Cohen; Ying Hu (SIAM J. Control. Optim., 2013)

Undiscounted Markov Chain BSDEs to Stopping Times. - Samuel N. Cohen (J. Appl. Probab., 2014)

Backward stochastic difference equations for dynamic convex risk measures on a binomial tree. - Robert J. Elliott; Tak Kuen Siu; Samuel N. Cohen (J. Appl. Probab., 2015)

Nash equilibria for nonzero-sum ergodic stochastic differential games. - Samuel N. Cohen; Victor Fedyashov (J. Appl. Probab., 2017)

Parameter Uncertainty in the Kalman-Bucy Filter. - Andrew L. Allan; Samuel N. Cohen (SIAM J. Control. Optim., 2019)

Identifiability in inverse reinforcement learning. - Haoyang Cao; Samuel N. Cohen; Lukasz Szpruch (NeurIPS, 2021)

Neural Q-learning for solving elliptic PDEs. - Samuel N. Cohen; Deqing Jiang; Justin A. Sirignano (CoRR, 2022)

Synthetic Data - what, why and how? - James Jordon; Lukasz Szpruch; Florimond Houssiau; Mirko Bottarelli; Giovanni Cherubin; Carsten Maple; Samuel N. Cohen; Adrian Weller (CoRR, 2022)

TAPAS: a Toolbox for Adversarial Privacy Auditing of Synthetic Data. - Florimond Houssiau; James Jordon; Samuel N. Cohen; Owen Daniel; Andrew Elliott; James Geddes; Callum D. Mole; Camila Rangel Smith; Lukasz Szpruch (CoRR, 2022)

A Framework for Auditable Synthetic Data Generation. - Florimond Houssiau; Samuel N. Cohen; Lukasz Szpruch; Owen Daniel; Michaela G. Lawrence; Robin Mitra; Henry Wilde; Callum D. Mole (CoRR, 2022)

Inefficiency of CFMs: Hedging Perspective and Agent-Based Simulations. - Samuel N. Cohen; Marc Sabate Vidales; David Siska; Lukasz Szpruch (FC Workshops, 2023)

Global Convergence of Deep Galerkin and PINNs Methods for Solving Partial Differential Equations. - Deqing Jiang; Justin A. Sirignano; Samuel N. Cohen (CoRR, 2023)

Mean-field Analysis of Generalization Errors. - Gholamali Aminian; Samuel N. Cohen; Lukasz Szpruch (CoRR, 2023)

Neural Q-learning for solving PDEs. - Samuel N. Cohen; Deqing Jiang; Justin A. Sirignano (J. Mach. Learn. Res., 2023)

Generalization Error of Graph Neural Networks in the Mean-field Regime. - Gholamali Aminian; Yixuan He; Gesine Reinert; Lukasz Szpruch; Samuel N. Cohen (ICML, 2024)

Generalization Error of the Tilted Empirical Risk. - Gholamali Aminian; Amir R. Asadi; Tian Li; Ahmad Beirami; Gesine Reinert; Samuel N. Cohen (CoRR, 2024)

Understanding Transfer Learning via Mean-field Analysis. - Gholamali Aminian; Lukasz Szpruch; Samuel N. Cohen (CoRR, 2024)

Optimal Adaptive Control with Separable Drift Uncertainty. - Samuel N. Cohen; Christoph Knochenhauer; Alexander Merkel (SIAM J. Control. Optim., 2025)

Neural Actor-Critic Methods for Hamilton-Jacobi-Bellman PDEs: Asymptotic Analysis and Numerical Studies. - Samuel N. Cohen; Jackson Hebner; Deqing Jiang; Justin A. Sirignano (CoRR, 2025)