Showing 1–20 of 20 results
/ Date/ Name
Mar 19, 2026Deep Hilbert--Galerkin Methods for Infinite-Dimensional PDEs and Optimal ControlAug 28, 2023Kernel Limit for a Class of Recurrent Neural Networks Trained on Ergodic Data SequencesMay 10, 2023Global Convergence of Deep Galerkin and PINNs Methods for Solving Partial Differential EquationsMar 4, 2023Dynamic Deep Learning LES Closures: Online Optimization With Embedded DNSAug 6, 2022Deep Learning Closure Models for Large-Eddy Simulation of Flows around Bluff BodiesJul 10, 2022A Forward Propagation Algorithm for Online Optimization of Nonlinear Stochastic Differential EquationsFeb 14, 2022Continuous-time stochastic gradient descent for optimizing over the stationary distribution of stochastic differential equationsAug 19, 2021Global Convergence of the ODE Limit for Online Actor-Critic Algorithms in Reinforcement LearningMay 18, 2021PDE-constrained Models with Neural Network Terms: Optimization and Global ConvergenceMay 3, 2021Embedded training of neural-network sub-grid-scale turbulence modelsNov 20, 2019DPM: A deep learning PDE augmentation method (with application to large-eddy simulation)Nov 13, 2019Asymptotics of Reinforcement Learning with Neural NetworksJul 9, 2019Scaling Limit of Neural Networks with the Xavier Initialization and Convergence to a Global MinimumMay 2, 2018Mean Field Analysis of Neural Networks: A Law of Large NumbersMar 19, 2018Universal features of price formation in financial markets: perspectives from Deep LearningOct 11, 2017Stochastic Gradient Descent in Continuous Time: A Central Limit TheoremAug 24, 2017DGM: A deep learning algorithm for solving partial differential equationsNov 17, 2016Stochastic Gradient Descent in Continuous TimeJul 8, 2016Deep Learning for Mortgage RiskJan 8, 2016Deep Learning for Limit Order Books