Valentin Duruisseaux

According to our database, Valentin Duruisseaux authored at least 16 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Fourier Neural Operators Explained: A Practical Perspective.

Valentin Duruisseaux, Jean Kossaifi, Anima Anandkumar

CoRR, December, 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, June, 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, June, 2025

Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning (Dataset).

Julius Berner, Miguel Liu-Schiaffini, Jean Kossaifi, Valentin Duruisseaux, Boris Bonev, Kamyar Azizzadenesheli, Anima Anandkumar

Dataset, June, 2025

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

Trans. Mach. Learn. Res., 2025

NOBLE - Neural Operator with Biologically-informed Latent Embeddings to Capture Experimental Variability in Biological Neuron Models.

Luca Ghafourpour, Valentin Duruisseaux, Bahareh Tolooshams, Philip Wong, Costas A. Anastassiou, Animashree Anandkumar

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2024

Projected Neural Differential Equations for Learning Constrained Dynamics.

Alistair White, Anna Büttner, Maximilian Gelbrecht, Valentin Duruisseaux, Niki Kilbertus, Frank Hellmann, Niklas Boers

CoRR, 2024

2023

Practical perspectives on symplectic accelerated optimization.

Valentin Duruisseaux, Melvin Leok

Optim. Methods Softw., November, 2023

An Operator Learning Framework for Spatiotemporal Super-resolution of Scientific Simulations.

Valentin Duruisseaux, Amit Chakraborty

CoRR, 2023

Simplifying Momentum-based Riemannian Submanifold Optimization.

Wu Lin, Valentin Duruisseaux, Melvin Leok, Frank Nielsen, Mohammad Emtiyaz Khan, Mark Schmidt

CoRR, 2023

Lie Group Forced Variational Integrator Networks for Learning and Control of Robot Systems.

Valentin Duruisseaux, Thai Duong, Melvin Leok, Nikolay Atanasov

Proceedings of the Learning for Dynamics and Control Conference, 2023

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

Proceedings of the International Conference on Machine Learning, 2023

2022

A Variational Formulation of Accelerated Optimization on Riemannian Manifolds.

Valentin Duruisseaux, Melvin Leok

SIAM J. Math. Data Sci., 2022

Accelerated Optimization on Riemannian Manifolds via Discrete Constrained Variational Integrators.

Valentin Duruisseaux, Melvin Leok

J. Nonlinear Sci., 2022

Approximation of nearly-periodic symplectic maps via structure-preserving neural networks.

Valentin Duruisseaux, Joshua W. Burby, Qi Tang

CoRR, 2022

2021

Adaptive Hamiltonian Variational Integrators and Applications to Symplectic Accelerated Optimization.

Valentin Duruisseaux, Jeremy Schmitt, Melvin Leok

SIAM J. Sci. Comput., 2021