Ariel Neufeld

632 total citations
29 papers, 236 citations indexed

About

Ariel Neufeld is a scholar working on Finance, Management Science and Operations Research and Computational Mechanics. According to data from OpenAlex, Ariel Neufeld has authored 29 papers receiving a total of 236 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Finance, 12 papers in Management Science and Operations Research and 7 papers in Computational Mechanics. Recurrent topics in Ariel Neufeld's work include Stochastic processes and financial applications (13 papers), Risk and Portfolio Optimization (8 papers) and Model Reduction and Neural Networks (6 papers). Ariel Neufeld is often cited by papers focused on Stochastic processes and financial applications (13 papers), Risk and Portfolio Optimization (8 papers) and Model Reduction and Neural Networks (6 papers). Ariel Neufeld collaborates with scholars based in Singapore, Switzerland and United States. Ariel Neufeld's co-authors include Marcel Nutz, Arnulf Jentzen, S. Becker, Patrick Cheridito, Christian Beck, Chong Liu, Kai Du, Ido Nevat, Matthew Ng and Gareth W. Peters and has published in prestigious journals such as Management Science, IEEE Transactions on Information Theory and Automatica.

In The Last Decade

Ariel Neufeld

22 papers receiving 223 citations

Peers

Ariel Neufeld

FINAN

MSOR

SNP

Xiaoli Wei China

Jean-François Chassagneux France

Côme Huré France

Jinniao Qiu Canada

David Šiška United Kingdom

Igor Cialenco United States

Mou-Hsiung Chang United States

Li‐Hsien Sun Taiwan

João Saúde Saudi Arabia

Lukas Gonon Switzerland

Xiaoli Wei China

Ariel Neufeld

131 ×1.0

FINAN

50 ×0.8

MSOR

24 ×0.4

SNP

33 ×0.6

41 ×1.3

Citations per year, relative to Ariel Neufeld Ariel Neufeld (= 1×) peers Xiaoli Wei

Countries citing papers authored by Ariel Neufeld

Since Specialization

Citations

This map shows the geographic impact of Ariel Neufeld's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ariel Neufeld with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ariel Neufeld more than expected).

Fields of papers citing papers by Ariel Neufeld

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ariel Neufeld. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ariel Neufeld. The network helps show where Ariel Neufeld may publish in the future.

Co-authorship network of co-authors of Ariel Neufeld

This figure shows the co-authorship network connecting the top 25 collaborators of Ariel Neufeld. A scholar is included among the top collaborators of Ariel Neufeld based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ariel Neufeld. Ariel Neufeld is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Neufeld, Ariel, et al.. (2025). Multilevel Picard approximation algorithm for semilinear partial integro-differential equations and its complexity analysis. Stochastic Partial Differential Equations Analysis and Computations. 13(3). 1220–1278. 1 indexed citations

Griffin, Paul, et al.. (2025). QuLTSF: Long-Term Time Series Forecasting with Quantum Machine Learning. 824–829. 1 indexed citations

Neufeld, Ariel, et al.. (2025). Universal approximation results for neural networks with non-polynomial activation function over non-compact domains. Analysis and Applications. 1–51.

Neufeld, Ariel, et al.. (2024). Full error analysis of the random deep splitting method for nonlinear parabolic PDEs and PIDEs. Communications in Nonlinear Science and Numerical Simulation. 143. 108556–108556. 2 indexed citations

Neufeld, Ariel, et al.. (2024). Bounding the difference between the values of robust and non-robust Markov decision problems. Journal of Applied Probability. 62(2). 558–571. 2 indexed citations

Neufeld, Ariel, et al.. (2024). Langevin Dynamics Based Algorithm e-THεO POULA for Stochastic Optimization Problems with Discontinuous Stochastic Gradient. Mathematics of Operations Research. 50(3). 2333–2374.

Neufeld, Ariel, et al.. (2024). Robust Q-learning algorithm for Markov decision processes under Wasserstein uncertainty. Automatica. 168. 111825–111825. 5 indexed citations

Neufeld, Ariel, Matthew Ng, & Ying Zhang. (2024). Non-asymptotic convergence bounds for modified tamed unadjusted Langevin algorithm in non-convex setting. Journal of Mathematical Analysis and Applications. 543(1). 128892–128892. 2 indexed citations

Neufeld, Ariel, et al.. (2024). Detecting Data-Driven Robust Statistical Arbitrage Strategies with Deep Neural Networks. SIAM Journal on Financial Mathematics. 15(2). 436–472.

10.

Neufeld, Ariel, et al.. (2024). Rectified deep neural networks overcome the curse of dimensionality when approximating solutions of McKean–Vlasov stochastic differential equations. Journal of Mathematical Analysis and Applications. 541(1). 128661–128661.

11.

Nevat, Ido, et al.. (2023). Binary spatial random field reconstruction from non-Gaussian inhomogeneous time-series observations. Journal of the Franklin Institute. 361(2). 612–636. 1 indexed citations

12.

Neufeld, Ariel, et al.. (2023). Markov decision processes under model uncertainty. Mathematical Finance. 33(3). 618–665. 5 indexed citations

13.

Neufeld, Ariel, et al.. (2023). A Bonus-Malus framework for cyber risk insurance and optimal cybersecurity provisioning. European Actuarial Journal. 14(2). 581–621. 2 indexed citations

14.

Beck, Christian, S. Becker, Patrick Cheridito, Arnulf Jentzen, & Ariel Neufeld. (2023). An efficient Monte Carlo scheme for Zakai equations. Communications in Nonlinear Science and Numerical Simulation. 126. 107438–107438. 1 indexed citations

15.

Neufeld, Ariel, et al.. (2023). Non-asymptotic estimates for TUSLA algorithm for non-convex learning with applications to neural networks with ReLU activation function. IMA Journal of Numerical Analysis. 44(3). 1464–1559. 2 indexed citations

16.

Neufeld, Ariel, et al.. (2022). Model-Free Bounds for Multi-Asset Options Using Option-Implied Information and Their Exact Computation. Management Science. 69(4). 2051–2068. 3 indexed citations

17.

Neufeld, Ariel, et al.. (2022). A Deep Learning Approach to Data-Driven Model-Free Pricing and to Martingale Optimal Transport. IEEE Transactions on Information Theory. 69(5). 3172–3189. 2 indexed citations

18.

Beck, Christian, S. Becker, Patrick Cheridito, Arnulf Jentzen, & Ariel Neufeld. (2021). Deep Splitting Method for Parabolic PDEs. SIAM Journal on Scientific Computing. 43(5). A3135–A3154. 62 indexed citations

19.

Neufeld, Ariel & Marcel Nutz. (2015). Nonlinear Lévy processes and their characteristics. Transactions of the American Mathematical Society. 369(1). 69–95. 36 indexed citations

20.

Neufeld, Ariel & Marcel Nutz. (2014). Measurability of semimartingale characteristics with respect to the probability law. Stochastic Processes and their Applications. 124(11). 3819–3845. 23 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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