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Justin A. Sirignano
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2020 – today
- 2024
- [i14]Samuel Chun-Hei Lam
, Justin A. Sirignano, Ziheng Wang:
Weak Convergence Analysis of Online Neural Actor-Critic Algorithms. CoRR abs/2403.16825 (2024) - 2023
- [j9]Justin A. Sirignano, Jonathan F. MacArt, Konstantinos Spiliopoulos:
PDE-constrained models with neural network terms: Optimization and global convergence. J. Comput. Phys. 481: 112016 (2023) - [j8]Samuel N. Cohen, Deqing Jiang, Justin A. Sirignano:
Neural Q-learning for solving PDEs. J. Mach. Learn. Res. 24: 236:1-236:49 (2023) - [i13]Justin A. Sirignano, Jonathan F. MacArt:
Dynamic Deep Learning LES Closures: Online Optimization With Embedded DNS. CoRR abs/2303.02338 (2023) - [i12]Deqing Jiang, Justin A. Sirignano, Samuel N. Cohen:
Global Convergence of Deep Galerkin and PINNs Methods for Solving Partial Differential Equations. CoRR abs/2305.06000 (2023) - [i11]Samuel Chun-Hei Lam
Kernel Limit of Recurrent Neural Networks Trained on Ergodic Data Sequences. CoRR abs/2308.14555 (2023) - 2022
- [j7]Justin A. Sirignano
Mean Field Analysis of Deep Neural Networks. Math. Oper. Res. 47(1): 120-152 (2022) - [i10]Ziheng Wang, Justin A. Sirignano:
Continuous-time stochastic gradient descent for optimizing over the stationary distribution of stochastic differential equations. CoRR abs/2202.06637 (2022) - [i9]Samuel N. Cohen, Deqing Jiang, Justin A. Sirignano:
Neural Q-learning for solving elliptic PDEs. CoRR abs/2203.17128 (2022) - [i8]Ziheng Wang, Justin A. Sirignano:
A Forward Propagation Algorithm for Online Optimization of Nonlinear Stochastic Differential Equations. CoRR abs/2207.04496 (2022) - [i7]Justin A. Sirignano, Jonathan F. MacArt:
Deep Learning Closure Models for Large-Eddy Simulation of Flows around Bluff Bodies. CoRR abs/2208.03498 (2022) - 2021
- [i6]Jonathan F. MacArt, Justin A. Sirignano, Jonathan B. Freund:
Embedded training of neural-network sub-grid-scale turbulence models. CoRR abs/2105.01030 (2021) - [i5]Justin A. Sirignano, Jonathan F. MacArt, Konstantinos Spiliopoulos:
PDE-constrained Models with Neural Network Terms: Optimization and Global Convergence. CoRR abs/2105.08633 (2021) - [i4]Ziheng Wang, Justin A. Sirignano:
Global Convergence of the ODE Limit for Online Actor-Critic Algorithms in Reinforcement Learning. CoRR abs/2108.08655 (2021) - 2020
- [j6]Justin A. Sirignano, Jonathan F. MacArt
DPM: A deep learning PDE augmentation method with application to large-eddy simulation. J. Comput. Phys. 423: 109811 (2020) - [j5]Justin A. Sirignano
Mean Field Analysis of Neural Networks: A Law of Large Numbers. SIAM J. Appl. Math. 80(2): 725-752 (2020)
2010 – 2019
- 2019
- [j4]Justin A. Sirignano, Kay Giesecke
Risk Analysis for Large Pools of Loans. Manag. Sci. 65(1): 107-121 (2019) - [i3]Justin A. Sirignano, Konstantinos Spiliopoulos:
Scaling Limit of Neural Networks with the Xavier Initialization and Convergence to a Global Minimum. CoRR abs/1907.04108 (2019) - [i2]Justin A. Sirignano, Konstantinos Spiliopoulos:
Asymptotics of Reinforcement Learning with Neural Networks. CoRR abs/1911.07304 (2019) - [i1]Jonathan B. Freund, Jonathan F. MacArt, Justin A. Sirignano:
DPM: A deep learning PDE augmentation method (with application to large-eddy simulation). CoRR abs/1911.09145 (2019) - 2018
- [j3]Justin A. Sirignano, Konstantinos Spiliopoulos:
DGM: A deep learning algorithm for solving partial differential equations. J. Comput. Phys. 375: 1339-1364 (2018) - 2017
- [j2]Justin A. Sirignano, Konstantinos Spiliopoulos:
Stochastic Gradient Descent in Continuous Time. SIAM J. Financial Math. 8(1): 933-961 (2017) - 2016
- [j1]Justin A. Sirignano, Gerry Tsoukalas
Large-Scale Loan Portfolio Selection. Oper. Res. 64(6): 1239-1255 (2016) - 2012
- [c1]Stephan E. Ludwig, Justin A. Sirignano, Ruojun Huang, George Papanicolaou:
A Forward-backward Algorithm for Stochastic Control Problems - Using the Stochastic Maximum Principle as an Alternative to Dynamic Programming. ICORES 2012: 83-89
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