Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Machine learning for high-dimensional dynamic stochastic economies
Simon Scheidegger, Ilias Bilionis
Journal of Computational Science (2019) Vol. 33, pp. 68-82
Closed Access | Times Cited: 56

Showing 1-25 of 56 citing articles:

Tackling Climate Change with Machine Learning
David Rolnick, Priya L. Donti, Lynn H. Kaack, et al.
ACM Computing Surveys (2022) Vol. 55, Iss. 2, pp. 1-96
Open Access | Times Cited: 487
Tackling Climate Change with Machine Learning
David Rolnick, Priya L. Donti, Lynn H. Kaack, et al.
arXiv (Cornell University) (2019)
Closed Access | Times Cited: 165
A review of the role of heuristics in stochastic optimisation: from metaheuristics to learnheuristics
Ángel A. Juan, Peter Keenan, Rafael Martı́, et al.
Annals of Operations Research (2021) Vol. 320, Iss. 2, pp. 831-861
Closed Access | Times Cited: 60
Financial Frictions and the Wealth Distribution
Jesús Fernández‐Villaverde, Samuel Hurtado, Galo Nuño
Econometrica (2023) Vol. 91, Iss. 3, pp. 869-901
Open Access | Times Cited: 39
AI for climate impacts: applications in flood risk
Anne Jones, Julian Kuehnert, Paolo Fraccaro, et al.
npj Climate and Atmospheric Science (2023) Vol. 6, Iss. 1
Open Access | Times Cited: 37
Machine Learning for Continuous-Time Finance
Victor Duarte, Diogo Duarte, Dejanir H. Silva
Review of Financial Studies (2024) Vol. 37, Iss. 11, pp. 3217-3271
Open Access | Times Cited: 9
A machine learning projection method for macro‐finance models
Vytautas Valaitis, Alessandro T. Villa
Quantitative Economics (2024) Vol. 15, Iss. 1, pp. 145-173
Open Access | Times Cited: 7
DEEP EQUILIBRIUM NETS
Marlon Azinovic, Luca Gaegauf, Simon Scheidegger
International Economic Review (2022) Vol. 63, Iss. 4, pp. 1471-1525
Open Access | Times Cited: 27
Probabilistic Machine Learning: New Frontiers for Modeling Consumers and their Choices
Ryan Dew, Nicolás Padilla, Lan Luo, et al.
International Journal of Research in Marketing (2024)
Closed Access | Times Cited: 4
Artificial intelligence as structural estimation: Deep Blue, Bonanza, and AlphaGo
Mitsuru Igami
Econometrics Journal (2020) Vol. 23, Iss. 3, pp. S1-S24
Open Access | Times Cited: 31
Machine learning and structural econometrics: contrasts and synergies
Fedor Iskhakov, John Rust, Bertel Schjerning
Econometrics Journal (2020) Vol. 23, Iss. 3, pp. S81-S124
Open Access | Times Cited: 30
Polynomial Chaos Expansion: Efficient Evaluation and Estimation of Computational Models
Daniel Fehrle, Christopher Heiberger, J. Huber
Computational Economics (2025)
Open Access
DeepHAM: A Global Solution Method for Heterogeneous Agent Models with Aggregate Shocks
Jiequn Han, Yucheng Yang, E Weinan
SSRN Electronic Journal (2021)
Open Access | Times Cited: 20
A simple but powerful simulated certainty equivalent approximation method for dynamic stochastic problems
Yongyang Cai, Kenneth L. Judd
Quantitative Economics (2023) Vol. 14, Iss. 2, pp. 651-687
Open Access | Times Cited: 7
Taming the Curse of Dimensionality: Quantitative Economics with Deep Learning
Jesús Fernández‐Villaverde, Galo Nuño, Jesse Perla
(2024)
Closed Access | Times Cited: 2
Optimizing high-dimensional stochastic forestry via reinforcement learning
Olli Tahvonen, Antti Suominen, Pekka Malo, et al.
Journal of Economic Dynamics and Control (2022) Vol. 145, pp. 104553-104553
Open Access | Times Cited: 11
Pareto-improving carbon-risk taxation
Laurence J. Kotlikoff, Felix Kübler, Andrey Polbin, et al.
Economic Policy (2021) Vol. 36, Iss. 107, pp. 551-589
Open Access | Times Cited: 14
Exploring the financial indicators to improve the pattern recognition of economic data based on machine learning
Xiaohui Wei, Wan-Ling Chen, Xiao Li
Neural Computing and Applications (2020) Vol. 33, Iss. 2, pp. 723-737
Closed Access | Times Cited: 13
Machine Learning Projection Methods for Macro-Finance Models
Vytautas Valaitis, Alessandro T. Villa
SSRN Electronic Journal (2018)
Closed Access | Times Cited: 13
Deep Equilibrium Nets
Marlon Azinovic, Luca Gaegauf, Simon Scheidegger
SSRN Electronic Journal (2019)
Closed Access | Times Cited: 13
Machine Learning for Dynamic Incentive Problems
Philipp Renner, Simon Scheidegger
SSRN Electronic Journal (2018)
Open Access | Times Cited: 13
Probabilistic Machine Learning: New Frontiers for Modeling Consumers and their Choices
Ryan Dew, Nicolás Padilla, Lan Luo, et al.
SSRN Electronic Journal (2024)
Closed Access | Times Cited: 1
Self-Justified Equilibria: Existence and Computation
Felix Kübler, Simon Scheidegger
SSRN Electronic Journal (2019)
Open Access | Times Cited: 12
Climate Change Through the Lens of Macroeconomic Modeling
Jesús Fernández‐Villaverde, Kenneth Gillingham, Simon Scheidegger
SSRN Electronic Journal (2024)
Closed Access | Times Cited: 1
Deep Structural Estimation: With an Application to Option Pricing
Hui Chen, Antoine Didisheim, Simon Scheidegger
SSRN Electronic Journal (2021)
Open Access | Times Cited: 9
Page 1 - Next Page

Scroll to top