| A variational formulation of accelerated optimization on Riemannian manifolds V Duruisseaux, M Leok SIAM Journal on Mathematics of Data Science 4 (2), 649-674, 2022 | 23 | 2022 |
| Adaptive Hamiltonian variational integrators and applications to symplectic accelerated optimization V Duruisseaux, J Schmitt, M Leok SIAM Journal on Scientific Computing 43 (4), A2949-A2980, 2021 | 22 | 2021 |
| Lie group forced variational integrator networks for learning and control of robot systems V Duruisseaux, TP Duong, M Leok, N Atanasov Learning for Dynamics and Control Conference, 731-744, 2023 | 12 | 2023 |
| Accelerated optimization on Riemannian manifolds via discrete constrained variational integrators V Duruisseaux, M Leok Journal of Nonlinear Science 32 (4), 42, 2022 | 12 | 2022 |
| Accelerated optimization on Riemannian manifolds via projected variational integrators V Duruisseaux, M Leok arXiv preprint arXiv:2201.02904, 2022 | 8 | 2022 |
| Approximation of nearly-periodic symplectic maps via structure-preserving neural networks V Duruisseaux, JW Burby, Q Tang Scientific reports 13 (1), 8351, 2023 | 6 | 2023 |
| Time-adaptive Lagrangian variational integrators for accelerated optimization on manifolds V Duruisseaux, M Leok arXiv preprint arXiv:2201.03774, 2022 | 6 | 2022 |
| Simplifying momentum-based positive-definite submanifold optimization with applications to deep learning W Lin, V Duruisseaux, M Leok, F Nielsen, ME Khan, M Schmidt International Conference on Machine Learning, 21026-21050, 2023 | 5 | 2023 |
| Accelerated optimization on Riemannian manifolds via projected variational integrators. 2022 V Duruisseaux, M Leok URL https://arxiv. org/abs/2201.02904 19, 0 | 5 | |
| Practical perspectives on symplectic accelerated optimization V Duruisseaux, M Leok Optimization Methods and Software 38 (6), 1230-1268, 2023 | 4 | 2023 |
| Approximation of nearly-periodic symplectic maps via structure-preserving neural networks V Duruisseaux, JW Burby, Q Tang arXiv preprint arXiv:2210.05087, 2022 | 2 | 2022 |
| Bistability, bifurcations and chaos in the Mackey-Glass equation V Duruisseaux, AR Humphries Journal of Computational Dynamics 9 (3), 421-450, 2022 | 2 | 2022 |
| Code Demonstration: Approximation of nearly-periodic symplectic maps via structure-preserving neural networks VN Duruisseaux, JW Burby, Q Tang Los Alamos National Laboratory (LANL), Los Alamos, NM (United States …, 2023 | 1 | 2023 |
| Simplifying Momentum-based Riemannian Submanifold Optimization. W Lin, V Duruisseaux, M Leok, F Nielsen, ME Khan, M Schmidt arXiv preprint arXiv:2302.09738, 2023 | 1 | 2023 |
| Variational accelerated optimization on Riemannian manifolds V Duruisseaux, M Leok IEICE Proceedings Series 71 (B1L-D-03), 2022 | 1 | 2022 |
| An Operator Learning Framework for Spatiotemporal Super-resolution of Scientific Simulations V Duruisseaux, A Chakraborty arXiv preprint arXiv:2311.02328, 2023 | | 2023 |
| Symplectic Numerical Integration at the Service of Accelerated Optimization and Structure-Preserving Dynamics Learning V Duruisseaux University of California, San Diego, 2023 | | 2023 |
| Practical Structured Riemannian Optimization with Momentum by using Generalized Normal Coordinates W Lin, V Duruisseaux, M Leok, F Nielsen, ME Khan, M Schmidt NeurIPS 2022 Workshop on Symmetry and Geometry in Neural Representations, 2022 | | 2022 |
| Towards Enforcing Hard Physics Constraints in Operator Learning Frameworks V Duruisseaux, M Liu-Schiaffini, J Berner, A Anandkumar ICML 2024 AI for Science Workshop, 0 | | |
