Samuel N. Cohen

According to our database, Samuel N. Cohen authored at least 18 papers between 2011 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Understanding Transfer Learning via Mean-field Analysis.

Gholamali Aminian, Lukasz Szpruch, Samuel N. Cohen

CoRR, 2024

Generalization Error of the Tilted Empirical Risk.

Gholamali Aminian, Amir R. Asadi, Tian Li, Ahmad Beirami, Gesine Reinert, Samuel N. Cohen

CoRR, 2024

Generalization Error of Graph Neural Networks in the Mean-field Regime.

Gholamali Aminian, Yixuan He, Gesine Reinert, Lukasz Szpruch, Samuel N. Cohen

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Neural Q-learning for solving PDEs.

Samuel N. Cohen, Deqing Jiang, Justin A. Sirignano

J. Mach. Learn. Res., 2023

Mean-field Analysis of Generalization Errors.

Gholamali Aminian, Samuel N. Cohen, Lukasz Szpruch

CoRR, 2023

Global Convergence of Deep Galerkin and PINNs Methods for Solving Partial Differential Equations.

Deqing Jiang, Justin A. Sirignano, Samuel N. Cohen

CoRR, 2023

Inefficiency of CFMs: Hedging Perspective and Agent-Based Simulations.

Samuel N. Cohen, Marc Sabate Vidales, David Siska, Lukasz Szpruch

Proceedings of the Financial Cryptography and Data Security. FC 2023 International Workshops, 2023

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

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

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

Neural Q-learning for solving elliptic PDEs.

Samuel N. Cohen, Deqing Jiang, Justin A. Sirignano

CoRR, 2022

2021

Identifiability in inverse reinforcement learning.

Haoyang Cao, Samuel N. Cohen, Lukasz Szpruch

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2019

Parameter Uncertainty in the Kalman-Bucy Filter.

Andrew L. Allan, Samuel N. Cohen

SIAM J. Control. Optim., 2019

2017

Nash equilibria for nonzero-sum ergodic stochastic differential games.

Samuel N. Cohen, Victor Fedyashov

J. Appl. Probab., 2017

2015

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

2014

Undiscounted Markov Chain BSDEs to Stopping Times.

Samuel N. Cohen

J. Appl. Probab., 2014

2013

Ergodic BSDEs Driven by Markov Chains.

Samuel N. Cohen, Ying Hu

SIAM J. Control. Optim., 2013

2011

Backward Stochastic Difference Equations and Nearly Time-Consistent Nonlinear Expectations.

Samuel N. Cohen, Robert J. Elliott

SIAM J. Control. Optim., 2011