| Fractional deep neural network via constrained optimization H Antil, R Khatri, R Löhner, D Verma Machine Learning: Science and Technology 2 (1), 015003, 2020 | 33 | 2020 |
| External optimal control of fractional parabolic PDEs H Antil, D Verma, M Warma ESAIM: Control, Optimisation and Calculus of Variations 26, 20, 2020 | 26 | 2020 |
| Novel deep neural networks for solving bayesian statistical inverse H Antil, HC Elman, A Onwunta, D Verma arXiv preprint arXiv:2102.03974, 2021 | 19 | 2021 |
| Optimal control of fractional elliptic PDEs with state constraints and characterization of the dual of fractional-order Sobolev spaces H Antil, D Verma, M Warma Journal of optimization theory and applications 186 (1), 1-23, 2020 | 18 | 2020 |
| Novel dnns for stiff odes with applications to chemically reacting flows TS Brown, H Antil, R Löhner, F Togashi, D Verma High Performance Computing: ISC High Performance Digital 2021 International …, 2021 | 9 | 2021 |
| Optimal Control of Fractional PDEs with State and Control Constraints H Antil, TS Brown, D Verma Pure and Applied Functional Analysis 2021, 2019 | 8* | 2019 |
| Optimal Control, Numerics, and Applications of Fractional PDEs H Antil, TS Brown, R Khatri, A Onwunta, D Verma, M Warma Handbook of Numerical Analysis, 2021 | 7 | 2021 |
| Deep neural nets with fixed bias configuration H Antil, TS Brown, R Löhner, F Togashi, D Verma arXiv preprint arXiv:2107.01308, 2021 | 6 | 2021 |
| A deep neural network approach for parameterized PDEs and Bayesian inverse problems H Antil, HC Elman, A Onwunta, D Verma Machine Learning: Science and Technology 4 (3), 035015, 2023 | 5 | 2023 |
| Efficient Neural Network Approaches for Conditional Optimal Transport with Applications in Bayesian Inference ZO Wang, R Baptista, Y Marzouk, L Ruthotto, D Verma arXiv preprint arXiv:2310.16975, 2023 | 4 | 2023 |
| Nondiffusive variational problems with distributional and weak gradient constraints H Antil, R Arndt, CN Rautenberg, D Verma Advances in Nonlinear Analysis 11 (1), 1466-1495, 2022 | 4 | 2022 |
| A neural network approach for stochastic optimal control X Li, D Verma, L Ruthotto arXiv preprint arXiv:2209.13104, 2022 | 3 | 2022 |
| Neural Network Approaches for Parameterized Optimal Control D Verma, N Winovich, L Ruthotto, BB Waanders arXiv preprint arXiv:2402.10033, 2024 | | 2024 |
| Learning Control Policies of Hodgkin-Huxley Neuronal Dynamics M Madondo, D Verma, L Ruthotto, NA Yong arXiv preprint arXiv:2311.07563, 2023 | | 2023 |
| A mixed finite element method using a biorthogonal system for optimal control problems governed by a biharmonic equation BP Lamichhane, N Nataraj, D Verma ANZIAMJ, 2023 | | 2023 |
| Data-Driven Control Strategies for PDE Environments using Reinforcement Learning. N Winovich, B van Bloemen Waanders, D Verma, L Ruthotto Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
| Reinforcement Learning for PDE Control Problems. N Winovich, B van Bloemen Waanders, D Verma, L Ruthotto Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
| Parallel Deep ResNets for Chemically Reacting Flows TS Brown, H Antil, R Lohner, D Verma, F Togashi AIAA SCITECH 2022 Forum, 1076, 2022 | | 2022 |
| Optimal Control Problems Constrained by Fractional PDES and Application to Deep Neural Networks D Verma George Mason University, 2021 | | 2021 |
| Deep Learning Meets Optimal Control and Dynamical System D Verma 2024 Joint Mathematics Meetings (JMM 2024), 0 | | |
Harbir AntilDirector, Center for Mathematics and Artificial Intelligence (CMAI), Professor of MathematicsVerified email at gmu.edu
