Showing 1–20 of 47 results
/ Date/ Name
Nov 13, 2023Learning Control Policies of Hodgkin-Huxley Neuronal DynamicsJan 13, 2026Differentiating through Stochastic Differential Equations: A PrimerOct 27, 2025Mixed Precision Training of Neural ODEsMay 21, 2018Never look back - A modified EnKF method and its application to the training of neural networks without back propagationMar 9, 2021An Introduction to Deep Generative ModelingMay 9, 2017Stable Architectures for Deep Neural NetworksJul 2, 2016Efficient Numerical Optimization For Susceptibility Artifact Correction Of EPI-MRIJul 10, 2023LSEMINK: A Modified Newton-Krylov Method for Log-Sum-Exp MinimizationMar 6, 2017Learning across scales - A multiscale method for Convolution Neural NetworksJul 24, 2017A Multiscale Method for Model Order Reduction in PDE Parameter EstimationJan 8, 2024Differential Equations for Continuous-Time Deep LearningMay 20, 2018Low-Cost Parameterizations of Deep Convolutional Neural NetworksAug 16, 2017Optimal Experimental Design for Constrained Inverse ProblemsApr 12, 2018Deep Neural Networks Motivated by Partial Differential EquationsDec 4, 2019A Machine Learning Framework for Solving High-Dimensional Mean Field Game and Mean Field Control ProblemsMay 28, 2017LAP: a Linearize and Project Method for Solving Inverse Problems with Coupled VariablesSep 27, 2022A Neural Network Approach for Stochastic Optimal ControlJul 26, 2020Train Like a (Var)Pro: Efficient Training of Neural Networks with Variable ProjectionMar 6, 2019IMEXnet: A Forward Stable Deep Neural NetworkMay 29, 2020OT-Flow: Fast and Accurate Continuous Normalizing Flows via Optimal Transport