| Wasserstein proximal algorithms for the Schrödinger bridge problem: Density control with nonlinear drift KF Caluya, A Halder IEEE Transactions on Automatic Control 67 (3), 1163-1178, 2021 | 53 | 2021 |
| Gradient flow algorithms for density propagation in stochastic systems KF Caluya, A Halder IEEE Transactions on Automatic Control 65 (10), 3991-4004, 2019 | 27 | 2019 |
| Reflected Schrödinger bridge: Density control with path constraints KF Caluya, A Halder 2021 American Control Conference (ACC), 1137-1142, 2021 | 24 | 2021 |
| Proximal recursion for solving the Fokker-Planck equation KF Caluya, A Halder 2019 American Control Conference (ACC), 4098-4103, 2019 | 17 | 2019 |
| Finite horizon density steering for multi-input state feedback linearizable systems KF Caluya, A Halder 2020 American Control Conference (ACC), 3577-3582, 2020 | 15 | 2020 |
| Finite horizon density control for static state feedback linearizable systems KF Caluya, A Halder arXiv preprint arXiv:1904.02272, 2019 | 13 | 2019 |
| Prediction and optimal feedback steering of probability density functions for safe automated driving S Haddad, KF Caluya, A Halder, B Singh 2021 American Control Conference (ACC), 2956-2961, 2021 | 9 | 2021 |
| Global convergence of second-order dynamics in two-layer neural networks W Krichene, KF Caluya, A Halder arXiv preprint arXiv:2007.06852, 2020 | 8 | 2020 |
| Hopfield neural network flow: A geometric viewpoint A Halder, KF Caluya, B Travacca, SJ Moura IEEE Transactions on Neural Networks and Learning Systems 31 (11), 4869-4880, 2020 | 7 | 2020 |
| Stochastic uncertainty propagation in power system dynamics using measure-valued proximal recursions A Halder, KF Caluya, P Ojaghi, X Geng IEEE Transactions on Power Systems, 2022 | 1 | 2022 |
| Generalized Gradient Flows for Density Prediction, Control and Learning K Caluya University of California, Santa Cruz, 2022 | | 2022 |
Abhishek HalderAssociate Professor, Iowa State UniversityDirección de correo verificada de iastate.edu
