Machine Learning in Macro Suggested Readings
- Will Artficial Intelligence Replace Computational Economists Any Time Soon? (2019) by Maliar, Maliar, and Winant
- Financial Frictions and the Wealth Distribution (2019) by Fernandez-Villaverde, Hurtado, and Nuno
- Machine Learning for High-Dimensional Dynamic Stochastic Economies (Journal of Computational Science, 2019) by Scheidegger and Bilionis
- Machine Learning for Continuous-Time Economics (2018) by Duarte
- Using Adaptive Sparse Grids to Solve High-Dimensional Dynamic Models (ECMA, 2017) by Brumm and Scheidegger
- Self-Justified Equilibria: Existence and Computation (2019) by Kubler and Scheidegger
- Deep Equilibrium Nets (2019) by Azinovic, Gaegauf, and Scheidegger
- Deep Learning Approximation for Stochastic Control Problems (2016) by Han and E
- Solving high-dimensional partial differential equations using deep learning (2018) by Han, Jentzen and E
- Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations (2017) by E, Han, and Jentzen
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