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Ariel Neufeld
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2020 – today
- 2024
- [j11]Ariel Neufeld, Julian Sester:
Robust Q-learning algorithm for Markov decision processes under Wasserstein uncertainty. Autom. 168: 111825 (2024) - [j10]Shunan Sheng, Qikun Xiang, Ido Nevat
, Ariel Neufeld
Binary spatial random field reconstruction from non-Gaussian inhomogeneous time-series observations. J. Frankl. Inst. 361(2): 612-636 (2024) - [j9]Ariel Neufeld
Detecting Data-Driven Robust Statistical Arbitrage Strategies with Deep Neural Networks. SIAM J. Financial Math. 15(2): 436-472 (2024) - [i31]Ariel Neufeld, Tuan Anh Nguyen:
Rectified deep neural networks overcome the curse of dimensionality in the numerical approximation of gradient-dependent semilinear heat equations. CoRR abs/2403.09200 (2024) - [i30]Daniel Bartl, Ariel Neufeld, Kyunghyun Park:
Numerical method for nonlinear Kolmogorov PDEs via sensitivity analysis. CoRR abs/2403.11910 (2024) - [i29]Ariel Neufeld, Philipp Schmocker, Sizhou Wu:
Full error analysis of the random deep splitting method for nonlinear parabolic PDEs and PIDEs with infinite activity. CoRR abs/2405.05192 (2024) - [i28]Luxu Liang, Ariel Neufeld, Ying Zhang:
Non-asymptotic convergence analysis of the stochastic gradient Hamiltonian Monte Carlo algorithm with discontinuous stochastic gradient with applications to training of ReLU neural networks. CoRR abs/2409.17107 (2024) - [i27]Ariel Neufeld, Tuan Anh Nguyen:
Multilevel Picard approximations and deep neural networks with ReLU, leaky ReLU, and softplus activation overcome the curse of dimensionality when approximating semilinear parabolic partial differential equations in Lp-sense. CoRR abs/2409.20431 (2024) - 2023
- [j8]Christian Beck, Sebastian Becker, Patrick Cheridito
An efficient Monte Carlo scheme for Zakai equations. Commun. Nonlinear Sci. Numer. Simul. 126: 107438 (2023) - [j7]Ariel Neufeld
Model-Free Bounds for Multi-Asset Options Using Option-Implied Information and Their Exact Computation. Manag. Sci. 69(4): 2051-2068 (2023) - [j6]Ariel Neufeld
A Deep Learning Approach to Data-Driven Model-Free Pricing and to Martingale Optimal Transport. IEEE Trans. Inf. Theory 69(5): 3172-3189 (2023) - [j5]Michel Baes
Low-Rank Plus Sparse Decomposition of Covariance Matrices Using Neural Network Parametrization. IEEE Trans. Neural Networks Learn. Syst. 34(1): 171-185 (2023) - [i26]Yongming Li, Ariel Neufeld:
Quantum Monte Carlo algorithm for solving Black-Scholes PDEs for high-dimensional option pricing in finance and its proof of overcoming the curse of dimensionality. CoRR abs/2301.09241 (2023) - [i25]Ariel Neufeld, Julian Sester:
Neural networks can detect model-free static arbitrage strategies. CoRR abs/2306.16422 (2023) - [i24]Ariel Neufeld, Qikun Xiang:
Feasible approximation of matching equilibria for large-scale matching for teams problems. CoRR abs/2308.03550 (2023) - [i23]Ariel Neufeld, Sizhou Wu:
Multilevel Picard algorithm for general semilinear parabolic PDEs with gradient-dependent nonlinearities. CoRR abs/2310.12545 (2023) - [i22]Ariel Neufeld, Tuan Anh Nguyen, Sizhou Wu:
Deep ReLU neural networks overcome the curse of dimensionality when approximating semilinear partial integro-differential equations. CoRR abs/2310.15581 (2023) - [i21]Ariel Neufeld, Tuan Anh Nguyen, Sizhou Wu:
Multilevel Picard approximations overcome the curse of dimensionality in the numerical approximation of general semilinear PDEs with gradient-dependent nonlinearities. CoRR abs/2311.11579 (2023) - [i20]Ariel Neufeld, Tuan Anh Nguyen:
Rectified deep neural networks overcome the curse of dimensionality when approximating solutions of McKean-Vlasov stochastic differential equations. CoRR abs/2312.07042 (2023) - [i19]Ariel Neufeld, Philipp Schmocker:
Universal Approximation Property of Random Neural Networks. CoRR abs/2312.08410 (2023) - 2022
- [i18]Ariel Neufeld, Qikun Xiang:
Numerical method for feasible and approximately optimal solutions of multi-marginal optimal transport beyond discrete measures. CoRR abs/2203.01633 (2022) - [i17]Ariel Neufeld, Julian Sester, Daiying Yin:
Detecting data-driven robust statistical arbitrage strategies with deep neural networks. CoRR abs/2203.03179 (2022) - [i16]Shunan Sheng, Qikun Xiang, Ido Nevat, Ariel Neufeld:
Binary Spatial Random Field Reconstruction from Non-Gaussian Inhomogeneous Time-series Observations. CoRR abs/2204.03343 (2022) - [i15]Ariel Neufeld, Qikun Xiang:
Numerical method for approximately optimal solutions of two-stage distributionally robust optimization with marginal constraints. CoRR abs/2205.05315 (2022) - [i14]Ariel Neufeld, Sizhou Wu:
Multilevel Picard approximation algorithm for semilinear partial integro-differential equations and its complexity analysis. CoRR abs/2205.09639 (2022) - [i13]Ariel Neufeld, Julian Sester, Mario Sikic:
Markov Decision Processes under Model Uncertainty. CoRR abs/2206.06109 (2022) - [i12]Ariel Neufeld, Matthew Ng Cheng En, Ying Zhang:
Non-asymptotic convergence bounds for modified tamed unadjusted Langevin algorithm in non-convex setting. CoRR abs/2207.02600 (2022) - [i11]Ariel Neufeld, Philipp Schmocker:
Chaotic Hedging with Iterated Integrals and Neural Networks. CoRR abs/2209.10166 (2022) - [i10]Ariel Neufeld, Julian Sester:
Robust Q-learning Algorithm for Markov Decision Processes under Wasserstein Uncertainty. CoRR abs/2210.00898 (2022) - [i9]Dong-Young Lim
Langevin dynamics based algorithm e-THεO POULA for stochastic optimization problems with discontinuous stochastic gradient. CoRR abs/2210.13193 (2022) - [i8]Christian Beck, Sebastian Becker, Patrick Cheridito, Arnulf Jentzen, Ariel Neufeld:
An efficient Monte Carlo scheme for Zakai equations. CoRR abs/2210.13530 (2022) - 2021
- [j4]Ariel Neufeld
Model-Free Price Bounds Under Dynamic Option Trading. SIAM J. Financial Math. 12(4): 1307-1339 (2021) - [j3]Christian Beck, Sebastian Becker, Patrick Cheridito, Arnulf Jentzen, Ariel Neufeld
Deep Splitting Method for Parabolic PDEs. SIAM J. Sci. Comput. 43(5): A3135-A3154 (2021) - [i7]Ariel Neufeld, Julian Sester:
A deep learning approach to data-driven model-free pricing and to martingale optimal transport. CoRR abs/2103.11435 (2021) - [i6]Dong-Young Lim, Ariel Neufeld, Sotirios Sabanis, Ying Zhang
Non-asymptotic estimates for TUSLA algorithm for non-convex learning with applications to neural networks with ReLU activation function. CoRR abs/2107.08649 (2021) - 2020
- [i5]Pushpendu Ghosh, Ariel Neufeld, Jajati Keshari Sahoo:
Forecasting directional movements of stock prices for intraday trading using LSTM and random forests. CoRR abs/2004.10178 (2020) - [i4]Christian Beck
Deep learning based numerical approximation algorithms for stochastic partial differential equations and high-dimensional nonlinear filtering problems. CoRR abs/2012.01194 (2020)
2010 – 2019
- 2019
- [j2]Ariel Neufeld
Nonconcave robust optimization with discrete strategies under Knightian uncertainty. Math. Methods Oper. Res. 90(2): 229-253 (2019) - [i3]Dominik Alfke, Weston Baines, Jan Blechschmidt, Mauricio J. del Razo Sarmina, Amnon Drory, Dennis Elbrächter, Nando Farchmin, Matteo Gambara, Silke Glas, Philipp Grohs, Peter Hinz, Danijel Kivaranovic, Christian Kümmerle, Gitta Kutyniok, Sebastian Lunz, Jan MacDonald, Ryan Malthaner, Gregory Naisat, Ariel Neufeld, Philipp Christian Petersen, Rafael Reisenhofer, Jun-Da Sheng, Laura Thesing, Philipp Trunschke, Johannes von Lindheim, David Weber, Melanie Weber:
The Oracle of DLphi. CoRR abs/1901.05744 (2019) - [i2]Christian Beck
Deep splitting method for parabolic PDEs. CoRR abs/1907.03452 (2019) - [i1]Michel Baes, Calypso Herrera, Ariel Neufeld, Pierre Ruyssen:
Low-Rank plus Sparse Decomposition of Covariance Matrices using Neural Network Parametrization. CoRR abs/1908.00461 (2019) - 2018
- [j1]Ariel Neufeld, Mario Sikic:
Robust Utility Maximization in Discrete-Time Markets with Friction. SIAM J. Control. Optim. 56(3): 1912-1937 (2018)
Coauthor Index
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