| 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 | 29 | 2021 |
| 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 | 27 | 2022 |
| FC-PINO: High Precision Physics-Informed Neural Operators via Fourier Continuation A Ganeshram, H Maust, V Duruisseaux, Z Li, Y Wang, D Leibovici, ... arXiv preprint arXiv:2211.15960, 2022 | 23 | 2022 |
| A library for learning neural operators J Kossaifi, N Kovachki, Z Li, D Pitt, M Liu-Schiaffini, V Duruisseaux, ... arXiv preprint arXiv:2412.10354, 2024 | 22 | 2024 |
| 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 | 22 | 2023 |
| Approximation of nearly-periodic symplectic maps via structure-preserving neural networks V Duruisseaux, JW Burby, Q Tang Scientific reports 13 (1), 8351, 2023 | 17 | 2023 |
| Accelerated optimization on Riemannian manifolds via discrete constrained variational integrators V Duruisseaux, M Leok Journal of Nonlinear Science 32 (4), 42, 2022 | 15 | 2022 |
| Practical perspectives on symplectic accelerated optimization V Duruisseaux, M Leok Optimization Methods and Software 38 (6), 1230-1268, 2023 | 14 | 2023 |
| 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 | 14 | 2023 |
| Time-adaptive Lagrangian variational integrators for accelerated optimization on manifolds V Duruisseaux, M Leok arXiv preprint arXiv:2201.03774, 2022 | 12 | 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, 2024 | 11 | 2024 |
| Bistability, bifurcations and chaos in the Mackey-Glass equation V Duruisseaux, AR Humphries arXiv preprint arXiv:2203.00181, 2022 | 9 | 2022 |
| Accelerated optimization on Riemannian manifolds via projected variational integrators V Duruisseaux, M Leok arXiv preprint arXiv:2201.02904, 2022 | 8 | 2022 |
| Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning J Berner, M Liu-Schiaffini, J Kossaifi, V Duruisseaux, B Bonev, ... arXiv preprint arXiv:2506.10973, 2025 | 7 | 2025 |
| Enabling automatic differentiation with mollified graph neural operators RY Lin, J Berner, V Duruisseaux, D Pitt, D Leibovici, J Kossaifi, ... arXiv preprint arXiv:2504.08277, 2025 | 5 | 2025 |
| Accelerated optimization on Riemannian manifolds via projected variational integrators. 2022 V Duruisseaux, M Leok URL https://arxiv. org/abs/2201.02904 19, 0 | 5 | |
| NOBLE--Neural Operator with Biologically-informed Latent Embeddings to Capture Experimental Variability in Biological Neuron Models L Ghafourpour, V Duruisseaux, B Tolooshams, PH Wong, CA Anastassiou, ... arXiv preprint arXiv:2506.04536, 2025 | 3 | 2025 |
| Projected neural differential equations for learning constrained dynamics A White, A Büttner, M Gelbrecht, V Duruisseaux, N Kilbertus, F Hellmann, ... arXiv preprint arXiv:2410.23667, 2024 | 2 | 2024 |
| Simplifying Momentum-based Riemannian Submanifold Optimization. W Lin, V Duruisseaux, M Leok, F Nielsen, ME Khan, M Schmidt arXiv preprint arXiv:2302.09738, 2023 | 2 | 2023 |
| 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 |
