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ORCIDStephan Eckstein
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2020 – today
- 2024
[j5]Stephan Eckstein, Marcel Nutz
:
Convergence Rates for Regularized Optimal Transport via Quantization. Math. Oper. Res. 49(2): 1223-1240 (2024)- 2023
- [j4]Stephan Eckstein, Armin Iske, Mathias Trabs:
Dimensionality Reduction and Wasserstein Stability for Kernel Regression. J. Mach. Learn. Res. 24: 334:1-334:35 (2023) - [c2]Yibo Yang, Stephan Eckstein, Marcel Nutz, Stephan Mandt:
Estimating the Rate-Distortion Function by Wasserstein Gradient Descent. NeurIPS 2023 - [i3]Yibo Yang, Stephan Eckstein, Marcel Nutz, Stephan Mandt:
Estimating the Rate-Distortion Function by Wasserstein Gradient Descent. CoRR abs/2310.18908 (2023) - 2022
- [j3]Daniel Bartl, Michael Kupper, Thibaut Lux, Antonis Papapantoleon, Stephan Eckstein:
Marginal and Dependence Uncertainty: Bounds, Optimal Transport, and Sharpness. SIAM J. Control. Optim. 60(1): 410-434 (2022) - [j2]Stephan Eckstein, Marcel Nutz:
Quantitative Stability of Regularized Optimal Transport and Convergence of Sinkhorn's Algorithm. SIAM J. Math. Anal. 54(6): 5922-5948 (2022) - [i2]Stephan Eckstein, Armin Iske, Mathias Trabs:
Dimensionality Reduction and Wasserstein Stability for Kernel Regression. CoRR abs/2203.09347 (2022) - 2021
- [j1]Stephan Eckstein, Gaoyue Guo, Tongseok Lim, Jan Oblój:
Robust Pricing and Hedging of Options on Multiple Assets and Its Numerics. SIAM J. Financial Math. 12(1): 158-188 (2021) - 2020
- [c1]Luca De Gennaro Aquino, Stephan Eckstein:
MinMax Methods for Optimal Transport and Beyond: Regularization, Approximation and Numerics. NeurIPS 2020 - [i1]Stephan Eckstein:
Lipschitz neural networks are dense in the set of all Lipschitz functions. CoRR abs/2009.13881 (2020)
Coauthor Index
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