Justin A. Sirignano

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 23

Top Topics

Solving Partial Differential Equations

Global Convergence

Top Venues

J. Comput. Phys.

Math. Oper. Res.

Publications

Samuel Chun-Hei Lam, Justin A. Sirignano, Ziheng Wang
Weak Convergence Analysis of Online Neural Actor-Critic Algorithms. CoRR (2024)
Justin A. Sirignano, Jonathan F. MacArt
Dynamic Deep Learning LES Closures: Online Optimization With Embedded DNS. CoRR (2023)
Justin A. Sirignano, Jonathan F. MacArt, Konstantinos Spiliopoulos
PDE-constrained models with neural network terms: Optimization and global convergence. J. Comput. Phys. 481 (2023)
Samuel Chun-Hei Lam, Justin A. Sirignano, Konstantinos Spiliopoulos
Kernel Limit of Recurrent Neural Networks Trained on Ergodic Data Sequences. CoRR (2023)
Deqing Jiang, Justin A. Sirignano, Samuel N. Cohen
Global Convergence of Deep Galerkin and PINNs Methods for Solving Partial Differential Equations. CoRR (2023)
Samuel N. Cohen, Deqing Jiang, Justin A. Sirignano
Neural Q-learning for solving PDEs. J. Mach. Learn. Res. 24 (2023)
Justin A. Sirignano, Jonathan F. MacArt
Deep Learning Closure Models for Large-Eddy Simulation of Flows around Bluff Bodies. CoRR (2022)
Justin A. Sirignano, Konstantinos Spiliopoulos
Mean Field Analysis of Deep Neural Networks. Math. Oper. Res. 47 (1) (2022)
Ziheng Wang, Justin A. Sirignano
Continuous-time stochastic gradient descent for optimizing over the stationary distribution of stochastic differential equations. CoRR (2022)
Samuel N. Cohen, Deqing Jiang, Justin A. Sirignano
Neural Q-learning for solving elliptic PDEs. CoRR (2022)
Ziheng Wang, Justin A. Sirignano
A Forward Propagation Algorithm for Online Optimization of Nonlinear Stochastic Differential Equations. CoRR (2022)
Ziheng Wang, Justin A. Sirignano
Global Convergence of the ODE Limit for Online Actor-Critic Algorithms in Reinforcement Learning. CoRR (2021)
Justin A. Sirignano, Jonathan F. MacArt, Konstantinos Spiliopoulos
PDE-constrained Models with Neural Network Terms: Optimization and Global Convergence. CoRR (2021)
Jonathan F. MacArt, Justin A. Sirignano, Jonathan B. Freund
Embedded training of neural-network sub-grid-scale turbulence models. CoRR (2021)
Justin A. Sirignano, Konstantinos Spiliopoulos
Mean Field Analysis of Neural Networks: A Law of Large Numbers. SIAM J. Appl. Math. 80 (2) (2020)
Justin A. Sirignano, Jonathan F. MacArt, Jonathan B. Freund
DPM: A deep learning PDE augmentation method with application to large-eddy simulation. J. Comput. Phys. 423 (2020)
Justin A. Sirignano, Konstantinos Spiliopoulos
Asymptotics of Reinforcement Learning with Neural Networks. CoRR (2019)
Jonathan B. Freund, Jonathan F. MacArt, Justin A. Sirignano
DPM: A deep learning PDE augmentation method (with application to large-eddy simulation). CoRR (2019)
Justin A. Sirignano, Konstantinos Spiliopoulos
Scaling Limit of Neural Networks with the Xavier Initialization and Convergence to a Global Minimum. CoRR (2019)
Justin A. Sirignano, Kay Giesecke
Risk Analysis for Large Pools of Loans. Manag. Sci. 65 (1) (2019)
Justin A. Sirignano, Konstantinos Spiliopoulos
DGM: A deep learning algorithm for solving partial differential equations. J. Comput. Phys. 375 (2018)
Justin A. Sirignano, Konstantinos Spiliopoulos
Stochastic Gradient Descent in Continuous Time. SIAM J. Financial Math. 8 (1) (2017)
Justin A. Sirignano, Gerry Tsoukalas, Kay Giesecke
Large-Scale Loan Portfolio Selection. Oper. Res. 64 (6) (2016)
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)