Justin A. Sirignano

35 papers C 1Journal 34

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Deep Hilbert-Galerkin Methods for Infinite-Dimensional PDEs and Optimal Control. CoRR Samuel N. Cohen, Filippo de Feo, Jackson Hebner, Justin A. Sirignano
2026	J	`jnl`	OGF: An online gradient flow method for optimizing the statistical steady-state time averages of unsteady turbulent flows. J. Comput. Phys. Tom Hickling, Jonathan F. MacArt, Justin A. Sirignano, Den Waidmann
2026	J	`jnl`	Online optimisation of machine learning collision models to accelerate direct molecular simulation of rarefied gas flows. J. Comput. Phys. Nicholas Daultry Ball, Jonathan F. MacArt, Justin A. Sirignano
2026	J	`jnl`	Scaling Effects and Uncertainty Quantification in Neural Actor Critic Algorithms. CoRR Nikos Georgoudios, Konstantinos Spiliopoulos, Justin A. Sirignano
2025	J	`jnl`	Convergence Analysis of Real-time Recurrent Learning (RTRL) for a class of Recurrent Neural Networks. CoRR Samuel Chun-Hei Lam, Justin A. Sirignano, Konstantinos Spiliopoulos
2025	J	`jnl`	Global Convergence of Adjoint-Optimized Neural PDEs. CoRR Konstantin Riedl, Justin A. Sirignano, Konstantinos Spiliopoulos
2025	J	`jnl`	Global Convergence of Adjoint-Optimized Neural PDEs. J. Mach. Learn. Res. Konstantin Riedl, Justin A. Sirignano, Konstantinos Spiliopoulos
2025	J	`jnl`	Neural Actor-Critic Methods for Hamilton-Jacobi-Bellman PDEs: Asymptotic Analysis and Numerical Studies. CoRR Samuel N. Cohen, Jackson Hebner, Deqing Jiang, Justin A. Sirignano
2025	J	`jnl`	OGF: An Online Gradient Flow Method for Optimizing the Statistical Steady-State Time Averages of Unsteady Turbulent Flows. CoRR Tom Hickling, Jonathan F. MacArt, Justin A. Sirignano, Den Waidmann
2025	J	`jnl`	Physics-Based Machine Learning Closures and Wall Models for Hypersonic Transition-Continuum Boundary Layer Predictions. CoRR Ashish S. Nair, Narendra Singh, Marco Panesi, Justin A. Sirignano, Jonathan F. MacArt
2025	J	`jnl`	oRANS: Online optimisation of RANS machine learning models with embedded DNS data generation. CoRR Daniel Dehtyriov, Jonathan F. MacArt, Justin A. Sirignano
2024	J	`jnl`	Weak Convergence Analysis of Online Neural Actor-Critic Algorithms. CoRR Samuel Chun-Hei Lam, Justin A. Sirignano, Ziheng Wang
2023	J	`jnl`	Dynamic Deep Learning LES Closures: Online Optimization With Embedded DNS. CoRR Justin A. Sirignano, Jonathan F. MacArt
2023	J	`jnl`	Global Convergence of Deep Galerkin and PINNs Methods for Solving Partial Differential Equations. CoRR Deqing Jiang, Justin A. Sirignano, Samuel N. Cohen
2023	J	`jnl`	Kernel Limit of Recurrent Neural Networks Trained on Ergodic Data Sequences. CoRR Samuel Chun-Hei Lam, Justin A. Sirignano, Konstantinos Spiliopoulos
2023	J	`jnl`	Neural Q-learning for solving PDEs. J. Mach. Learn. Res. Samuel N. Cohen, Deqing Jiang, Justin A. Sirignano
2023	J	`jnl`	PDE-constrained models with neural network terms: Optimization and global convergence. J. Comput. Phys. Justin A. Sirignano, Jonathan F. MacArt, Konstantinos Spiliopoulos
2022	J	`jnl`	A Forward Propagation Algorithm for Online Optimization of Nonlinear Stochastic Differential Equations. CoRR Ziheng Wang, Justin A. Sirignano
2022	J	`jnl`	Continuous-time stochastic gradient descent for optimizing over the stationary distribution of stochastic differential equations. CoRR Ziheng Wang, Justin A. Sirignano
2022	J	`jnl`	Deep Learning Closure Models for Large-Eddy Simulation of Flows around Bluff Bodies. CoRR Justin A. Sirignano, Jonathan F. MacArt
2022	J	`jnl`	Mean Field Analysis of Deep Neural Networks. Math. Oper. Res. Justin A. Sirignano, Konstantinos Spiliopoulos
2022	J	`jnl`	Neural Q-learning for solving elliptic PDEs. CoRR Samuel N. Cohen, Deqing Jiang, Justin A. Sirignano
2021	J	`jnl`	Embedded training of neural-network sub-grid-scale turbulence models. CoRR Jonathan F. MacArt, Justin A. Sirignano, Jonathan B. Freund
2021	J	`jnl`	Global Convergence of the ODE Limit for Online Actor-Critic Algorithms in Reinforcement Learning. CoRR Ziheng Wang, Justin A. Sirignano
2021	J	`jnl`	PDE-constrained Models with Neural Network Terms: Optimization and Global Convergence. CoRR Justin A. Sirignano, Jonathan F. MacArt, Konstantinos Spiliopoulos
2020	J	`jnl`	DPM: A deep learning PDE augmentation method with application to large-eddy simulation. J. Comput. Phys. Justin A. Sirignano, Jonathan F. MacArt, Jonathan B. Freund
2020	J	`jnl`	Mean Field Analysis of Neural Networks: A Law of Large Numbers. SIAM J. Appl. Math. Justin A. Sirignano, Konstantinos Spiliopoulos
2019	J	`jnl`	Asymptotics of Reinforcement Learning with Neural Networks. CoRR Justin A. Sirignano, Konstantinos Spiliopoulos
2019	J	`jnl`	DPM: A deep learning PDE augmentation method (with application to large-eddy simulation). CoRR Jonathan B. Freund, Jonathan F. MacArt, Justin A. Sirignano
2019	J	`jnl`	Risk Analysis for Large Pools of Loans. Manag. Sci. Justin A. Sirignano, Kay Giesecke
2019	J	`jnl`	Scaling Limit of Neural Networks with the Xavier Initialization and Convergence to a Global Minimum. CoRR Justin A. Sirignano, Konstantinos Spiliopoulos
2018	J	`jnl`	DGM: A deep learning algorithm for solving partial differential equations. J. Comput. Phys. Justin A. Sirignano, Konstantinos Spiliopoulos
2017	J	`jnl`	Stochastic Gradient Descent in Continuous Time. SIAM J. Financial Math. Justin A. Sirignano, Konstantinos Spiliopoulos
2016	J	`jnl`	Large-Scale Loan Portfolio Selection. Oper. Res. Justin A. Sirignano, Gerry Tsoukalas, Kay Giesecke
2012	C	`conf`	A Forward-backward Algorithm for Stochastic Control Problems - Using the Stochastic Maximum Principle as an Alternative to Dynamic Programming. ICORES Stephan E. Ludwig, Justin A. Sirignano, Ruojun Huang, George Papanicolaou