Ariel Neufeld - RankMe

54 papers Journal 53Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Approximation rates of quantum neural networks for periodic functions via Jackson's inequality. CoRR Ariel Neufeld, Philipp Schmocker, Viet Khoa Tran
2025	J	`jnl`	Bounding the difference between the values of robust and non-robust Markov decision problems. J. Appl. Probab. Ariel Neufeld, Julian Sester
2025	J	`jnl`	Full error analysis of the random deep splitting method for nonlinear parabolic PDEs and PIDEs. Commun. Nonlinear Sci. Numer. Simul. Ariel Neufeld, Philipp Schmocker, Sizhou Wu
2025	J	`jnl`	Generative Neural Operators of Log-Complexity Can Simultaneously Solve Infinitely Many Convex Programs. CoRR Anastasis Kratsios, Ariel Neufeld, Philipp Schmocker
2025	J	`jnl`	Langevin Dynamics Based Algorithm e-TH Math. Oper. Res. Dong-Young Lim, Ariel Neufeld, Sotirios Sabanis, Ying Zhang
2025	J	`jnl`	Multilevel Picard approximations for McKean-Vlasov stochastic differential equations with nonconstant diffusion. CoRR Ariel Neufeld, Tuan Anh Nguyen, Philipp Schmocker
2025	J	`jnl`	Multilevel Picard approximations overcome the curse of dimensionality in the numerical approximation of general semilinear PDEs with gradient-dependent nonlinearities. J. Complex. Ariel Neufeld, Tuan Anh Nguyen, Sizhou Wu
2025	J	`jnl`	Provably convergent stochastic fixed-point algorithm for free-support Wasserstein barycenter of continuous non-parametric measures. CoRR Zeyi Chen, Ariel Neufeld, Qikun Xiang
2025	—	`conf`	QuLTSF: Long-Term Time Series Forecasting with Quantum Machine Learning. ICAART (1) Hari Hara Suthan Chittoor, Paul Robert Griffin, Ariel Neufeld, Jayne Thompson, Mile Gu
2024	J	`jnl`	Binary spatial random field reconstruction from non-Gaussian inhomogeneous time-series observations. J. Frankl. Inst. Shunan Sheng, Qikun Xiang, Ido Nevat, Ariel Neufeld
2024	J	`jnl`	Detecting Data-Driven Robust Statistical Arbitrage Strategies with Deep Neural Networks. SIAM J. Financial Math. Ariel Neufeld, Julian Sester, Daiying Yin
2024	J	`jnl`	Full error analysis of the random deep splitting method for nonlinear parabolic PDEs and PIDEs with infinite activity. CoRR Ariel Neufeld, Philipp Schmocker, Sizhou Wu
2024	J	`jnl`	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 L CoRR Ariel Neufeld, Tuan Anh Nguyen
2024	J	`jnl`	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 Luxu Liang, Ariel Neufeld, Ying Zhang
2024	J	`jnl`	Numerical method for nonlinear Kolmogorov PDEs via sensitivity analysis. CoRR Daniel Bartl, Ariel Neufeld, Kyunghyun Park
2024	J	`jnl`	QuLTSF: Long-Term Time Series Forecasting with Quantum Machine Learning. CoRR Hari Hara Suthan Chittoor, Paul Robert Griffin, Ariel Neufeld, Jayne Thompson, Mile Gu
2024	J	`jnl`	Rectified deep neural networks overcome the curse of dimensionality in the numerical approximation of gradient-dependent semilinear heat equations. CoRR Ariel Neufeld, Tuan Anh Nguyen
2024	J	`jnl`	Robust Q-learning algorithm for Markov decision processes under Wasserstein uncertainty. Autom. Ariel Neufeld, Julian Sester
2024	J	`jnl`	Solving stochastic partial differential equations using neural networks in the Wiener chaos expansion. CoRR Ariel Neufeld, Philipp Schmocker
2024	J	`jnl`	Universal approximation results for neural networks with non-polynomial activation function over non-compact domains. CoRR Ariel Neufeld, Philipp Schmocker
2023	J	`jnl`	A Deep Learning Approach to Data-Driven Model-Free Pricing and to Martingale Optimal Transport. IEEE Trans. Inf. Theory Ariel Neufeld, Julian Sester
2023	J	`jnl`	An efficient Monte Carlo scheme for Zakai equations. Commun. Nonlinear Sci. Numer. Simul. Christian Beck, Sebastian Becker, Patrick Cheridito, Arnulf Jentzen, Ariel Neufeld
2023	J	`jnl`	Deep ReLU neural networks overcome the curse of dimensionality when approximating semilinear partial integro-differential equations. CoRR Ariel Neufeld, Tuan Anh Nguyen, Sizhou Wu
2023	J	`jnl`	Feasible approximation of matching equilibria for large-scale matching for teams problems. CoRR Ariel Neufeld, Qikun Xiang
2023	J	`jnl`	Low-Rank Plus Sparse Decomposition of Covariance Matrices Using Neural Network Parametrization. IEEE Trans. Neural Networks Learn. Syst. Michel Baes, Calypso Herrera, Ariel Neufeld, Pierre Ruyssen
2023	J	`jnl`	Model-Free Bounds for Multi-Asset Options Using Option-Implied Information and Their Exact Computation. Manag. Sci. Ariel Neufeld, Antonis Papapantoleon, Qikun Xiang
2023	J	`jnl`	Multilevel Picard algorithm for general semilinear parabolic PDEs with gradient-dependent nonlinearities. CoRR Ariel Neufeld, Sizhou Wu
2023	J	`jnl`	Multilevel Picard approximations overcome the curse of dimensionality in the numerical approximation of general semilinear PDEs with gradient-dependent nonlinearities. CoRR Ariel Neufeld, Tuan Anh Nguyen, Sizhou Wu
2023	J	`jnl`	Neural networks can detect model-free static arbitrage strategies. CoRR Ariel Neufeld, Julian Sester
2023	J	`jnl`	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 Yongming Li, Ariel Neufeld
2023	J	`jnl`	Rectified deep neural networks overcome the curse of dimensionality when approximating solutions of McKean-Vlasov stochastic differential equations. CoRR Ariel Neufeld, Tuan Anh Nguyen
2023	J	`jnl`	Universal Approximation Property of Random Neural Networks. CoRR Ariel Neufeld, Philipp Schmocker
2022	J	`jnl`	An efficient Monte Carlo scheme for Zakai equations. CoRR Christian Beck, Sebastian Becker, Patrick Cheridito, Arnulf Jentzen, Ariel Neufeld
2022	J	`jnl`	Binary Spatial Random Field Reconstruction from Non-Gaussian Inhomogeneous Time-series Observations. CoRR Shunan Sheng, Qikun Xiang, Ido Nevat, Ariel Neufeld
2022	J	`jnl`	Chaotic Hedging with Iterated Integrals and Neural Networks. CoRR Ariel Neufeld, Philipp Schmocker
2022	J	`jnl`	Detecting data-driven robust statistical arbitrage strategies with deep neural networks. CoRR Ariel Neufeld, Julian Sester, Daiying Yin
2022	J	`jnl`	Langevin dynamics based algorithm e-THεO POULA for stochastic optimization problems with discontinuous stochastic gradient. CoRR Dong-Young Lim, Ariel Neufeld, Sotirios Sabanis, Ying Zhang
2022	J	`jnl`	Markov Decision Processes under Model Uncertainty. CoRR Ariel Neufeld, Julian Sester, Mario Sikic
2022	J	`jnl`	Multilevel Picard approximation algorithm for semilinear partial integro-differential equations and its complexity analysis. CoRR Ariel Neufeld, Sizhou Wu
2022	J	`jnl`	Non-asymptotic convergence bounds for modified tamed unadjusted Langevin algorithm in non-convex setting. CoRR Ariel Neufeld, Matthew Ng Cheng En, Ying Zhang
2022	J	`jnl`	Numerical method for approximately optimal solutions of two-stage distributionally robust optimization with marginal constraints. CoRR Ariel Neufeld, Qikun Xiang
2022	J	`jnl`	Numerical method for feasible and approximately optimal solutions of multi-marginal optimal transport beyond discrete measures. CoRR Ariel Neufeld, Qikun Xiang
2022	J	`jnl`	Robust Q-learning Algorithm for Markov Decision Processes under Wasserstein Uncertainty. CoRR Ariel Neufeld, Julian Sester
2021	J	`jnl`	A deep learning approach to data-driven model-free pricing and to martingale optimal transport. CoRR Ariel Neufeld, Julian Sester
2021	J	`jnl`	Deep Splitting Method for Parabolic PDEs. SIAM J. Sci. Comput. Christian Beck, Sebastian Becker, Patrick Cheridito, Arnulf Jentzen, Ariel Neufeld
2021	J	`jnl`	Model-Free Price Bounds Under Dynamic Option Trading. SIAM J. Financial Math. Ariel Neufeld, Julian Sester
2021	J	`jnl`	Non-asymptotic estimates for TUSLA algorithm for non-convex learning with applications to neural networks with ReLU activation function. CoRR Dong-Young Lim, Ariel Neufeld, Sotirios Sabanis, Ying Zhang
2020	J	`jnl`	Deep learning based numerical approximation algorithms for stochastic partial differential equations and high-dimensional nonlinear filtering problems. CoRR Christian Beck, Sebastian Becker, Patrick Cheridito, Arnulf Jentzen, Ariel Neufeld
2020	J	`jnl`	Forecasting directional movements of stock prices for intraday trading using LSTM and random forests. CoRR Pushpendu Ghosh, Ariel Neufeld, Jajati Keshari Sahoo
2019	J	`jnl`	Deep splitting method for parabolic PDEs. CoRR Christian Beck, Sebastian Becker, Patrick Cheridito, Arnulf Jentzen, Ariel Neufeld
2019	J	`jnl`	Low-Rank plus Sparse Decomposition of Covariance Matrices using Neural Network Parametrization. CoRR Michel Baes, Calypso Herrera, Ariel Neufeld, Pierre Ruyssen
2019	J	`jnl`	Nonconcave robust optimization with discrete strategies under Knightian uncertainty. Math. Methods Oper. Res. Ariel Neufeld, Mario Sikic
2019	J	`jnl`	The Oracle of DLphi. CoRR 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
2018	J	`jnl`	Robust Utility Maximization in Discrete-Time Markets with Friction. SIAM J. Control. Optim. Ariel Neufeld, Mario Sikic