Fetching the paper…
Reading the bibliography…
We develop a methodology that utilizes deep learning to simultaneously solve and estimate canonical continuous-time general equilibrium models in financial economics.
Entry, Exit, and Firm Dynamics in Long Run Equilibrium
Hopenhayn, H. A. (1992) · 1992
Earlier work this paper cites.
Corporate debt value, bond covenants, and optimal capital structure
Leland, H. E. (1994) · 1994
Earlier work this paper cites.
The Fokker-Planck equation: Methods of solution and applications
Risken, H. (1996) · 1996
Earlier work this paper cites.
Brownian motion and stochastic calculus
Karatzas, I. and Shreve, S. (1998) · 1998
Earlier work this paper cites.
Equilibrium cross section of returns
Gomes, J., Kogan, L., and Zhang, L. (2003) · 2003
Earlier work this paper cites.
Financial constraints risk
Whited, T. M. and Wu, G. (2006) · 2006
Earlier work this paper cites.
How costly is external financing? evidence from a structural estimation
Hennessy, C. A. and Whited, T. M. (2007) · 2007
Earlier work this paper cites.
Multi-scale deep neural network (MscaleDNN) methods for oscillatory stokes flows in complex domains
Wang, B., Zhang, W., and Cai, W. (2020) · 2009
Earlier work this paper cites.
Practical bayesian optimization of machine learning algorithms
Snoek, J., Larochelle, H., and Adams, R. P. (2012) · 2012
Earlier work this paper cites.
Intermediary asset pricing
He, Z. and Krishnamurthy, A. (2013) · 2013
Earlier work this paper cites.
A macroeconomic model with a financial sector
Brunnermeier, M. K. and Sannikov, Y. (2014) · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Kingma, D. P. and Ba, J. (2014) · 2014
Earlier work this paper cites.
Resource allocation within firms and financial market dislocation: Evidence from diversified conglomerates
Matvos, G. and Seru, A. (2014) · 2014
Earlier work this paper cites.
Stochastic processes and applications: diffusion processes, the Fokker-Planck and Langevin equations
Pavliotis, G. A. (2014) · 2014
Earlier work this paper cites.
Searching for activation functions
Ramachandran, P., Zoph, B., and Le, Q. V. (2017) · 2017
Earlier work this paper cites.
Banks, liquidity management and monetary policy
Bianchi, J. and Bigio, S. (2018) · 2018
Earlier work this paper cites.
A model of monetary policy and risk premia
Drechsler, I., Savov, A., and Schnabl, P. (2018) · 2018
Cited alongside, same era.
Machine learning for continuous-time economics
Duarte, V. (2018) · 2018
Cited alongside, same era.
Comparative valuation dynamics in models with financing restrictions
Hansen, L. P., Khorrami, P., and Tourre, F. (2018) · 2018
Cited alongside, same era.
Banking and shadow banking
Huang, J. (2018) · 2018
Cited alongside, same era.
Optimal regulation of financial intermediaries
Di Tella, S. (2019) · 2019
Cited alongside, same era.
Public liquidity and financial crises
Li, W. (2019) · 2019
Cited alongside, same era.
fpinns: Fractional physics-informed neural networks
Physics-informed neural networks for cardiac activation mapping
Sahli Costabal, F., Yang, Y., Perdikaris, P., Hurtado, D. E., and Kuhl, E. (2020) · 2020
Later among the works it cites.
Physics-informed deep neural networks for learning parameters and constitutive relationships in subsurface flow problems
Tartakovsky, A. M., Marrero, C. O., Perdikaris, P., Tartakovsky, G. D., and Barajas-Solano, D. (2020) · 2020
Later among the works it cites.
Systems biology informed deep learning for inferring parameters and hidden dynamics
Yazdani, A., Lu, L., Raissi, M., and Karniadakis, G. E. (2020) · 2020
Later among the works it cites.
Deep structural estimation: With an application to option pricing
Chen, H., Didisheim, A., and Scheidegger, S. (2021) · 2021
Later among the works it cites.
DeepHAM: A global solution method for heterogeneous agent models with aggregate shocks
Han, J., Yang, Y., and E, W. (2021) · 2021
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Pang, G., Lu, L., and Karniadakis, G. E. (2019) · 2019
Cited alongside, same era.
Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
Raissi, M., Perdikaris, P., and Karniadakis, G. (2019) · 2019
Cited alongside, same era.
Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems
Zhang, D., Lu, L., Guo, L., and Karniadakis, G. E. (2019) · 2019
Cited alongside, same era.
Physics-informed neural networks for inverse problems in nano-optics and metamaterials
Chen, Y., Lu, L., Karniadakis, G. E., and Dal Negro, L. (2020) · 2020
Cited alongside, same era.
Solving high-dimensional dynamic programming problems using deep learning
Fernandez-Villaverde, J., Nuno, G., Sorg-Langhans, G., and Vogler, M. (2020) · 2020
Cited alongside, same era.
A macro-finance model with realistic crisis dynamics
Gopalakrishna, G. (2020) · 2020
Cited alongside, same era.
Later among the works it cites.
Physics-informed machine learning
Karniadakis, G. E., Kevrekidis, I. G., Lu, L., Perdikaris, P., Wang, S., and Yang, L. (2021) · 2021
Later among the works it cites.
Deep learning for solving dynamic economic models
Maliar, L., Maliar, S., and Winant, P. (2021) · 2021
Later among the works it cites.
Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems
Yu, J., Lu, L., Meng, X., and Karniadakis, G. E. (2021) · 2021
Later among the works it cites.
Deep equilibrium nets
Azinovic, M., Gaegauf, L., and Scheidegger, S. (2022) · 2022
Later among the works it cites.
A probabilistic solution to high-dimensional continuous-time macro-finance models
Huang, J. (2022) · 2022
Later among the works it cites.
Wu, W., Daneker, M., Jolley, M. A., Turner, K. T., and Lu, L. (2022) · 2022
Later among the works it cites.
Systems biology: Identifiability analysis and parameter identification via systems-biology-informed neural networks
Daneker, M., Zhang, Z., Karniadakis, G. E., and Lu, L. (2023) · 2023
Closest in time.
A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks
Wu, C., Zhu, M., Tan, Q., Kartha, Y., and Lu, L. (2023) · 2023
Closest in time.
Partial differential equation models in macroeconomics
Achdou, Y., Buera, F. J., Lasry, J.-M., Lions, P.-L., and Moll, B. (2014) · 2028
Closest in time.
Banking, liquidity, and bank runs in an infinite horizon economy
Gertler, M. and Kiyotaki, N. (2015) · 2043
Closest in time.
The dynamics of inequality
Gabaix, X., Lasry, J.-M., Lions, P.-L., and Moll, B. (2016) · 2071
Closest in time.