Adaptive Hamiltonian Variational Integrators and Applications to Symplectic Accelerated Optimization. - Valentin Duruisseaux; Jeremy Schmitt; Melvin Leok (SIAM J. Sci. Comput., 2021)

Approximation of nearly-periodic symplectic maps via structure-preserving neural networks. - Valentin Duruisseaux; Joshua W. Burby; Qi Tang 001 (CoRR, 2022)

Accelerated Optimization on Riemannian Manifolds via Discrete Constrained Variational Integrators. - Valentin Duruisseaux; Melvin Leok (J. Nonlinear Sci., 2022)

A Variational Formulation of Accelerated Optimization on Riemannian Manifolds. - Valentin Duruisseaux; Melvin Leok (SIAM J. Math. Data Sci., 2022)

Simplifying Momentum-based Positive-definite Submanifold Optimization with Applications to Deep Learning. - Wu Lin; Valentin Duruisseaux; Melvin Leok; Frank Nielsen; Mohammad Emtiyaz Khan; Mark Schmidt 001 (ICML, 2023)

Lie Group Forced Variational Integrator Networks for Learning and Control of Robot Systems. - Valentin Duruisseaux; Thai Duong 001; Melvin Leok; Nikolay Atanasov 001 (L4DC, 2023)

Simplifying Momentum-based Riemannian Submanifold Optimization. - Wu Lin; Valentin Duruisseaux; Melvin Leok; Frank Nielsen; Mohammad Emtiyaz Khan; Mark Schmidt 001 (CoRR, 2023)

An Operator Learning Framework for Spatiotemporal Super-resolution of Scientific Simulations. - Valentin Duruisseaux; Amit Chakraborty (CoRR, 2023)

Practical perspectives on symplectic accelerated optimization. - Valentin Duruisseaux; Melvin Leok (Optim. Methods Softw., 2023)

Projected Neural Differential Equations for Learning Constrained Dynamics. - Alistair White; Anna Büttner; Maximilian Gelbrecht; Valentin Duruisseaux; Niki Kilbertus; Frank Hellmann; Niklas Boers (CoRR, 2024)

Enabling Automatic Differentiation with Mollified Graph Neural Operators. - Ryan Y. Lin; Julius Berner; Valentin Duruisseaux; David Pitt; Daniel V. Leibovici; Jean Kossaifi; Kamyar Azizzadenesheli; Anima Anandkumar (CoRR, 2025)

NOBLE - Neural Operator with Biologically-informed Latent Embeddings to Capture Experimental Variability in Biological Neuron Models. - Luca Ghafourpour; Valentin Duruisseaux; Bahareh Tolooshams; Philip H. Wong; Costas A. Anastassiou; Anima Anandkumar (CoRR, 2025)

Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning. - Julius Berner; Miguel Liu-Schiaffini; Jean Kossaifi; Valentin Duruisseaux; Boris Bonev; Kamyar Azizzadenesheli; Anima Anandkumar (CoRR, 2025)