9 citations · 46 across the 17 of their papers we have counts for
7 papers · 1 filter
Lie Group Forced Variational Integrator Networks for Learning and Control of Robot Systems
Valentin Duruisseaux, Thai Duong, Melvin Leok +1
Incorporating prior knowledge of physics laws and structural properties of dynamical systems into the design of deep learning architectures has proven to be a powerful technique fo…
FC-PINO: High Precision Physics-Informed Neural Operators via Fourier Continuation
Adarsh Ganeshram, Haydn Maust, Valentin Duruisseaux +6
The physics-informed neural operator (PINO) is a machine learning paradigm that has demonstrated promising results for learning solutions to partial differential equations (PDEs).…
Approximation of nearly-periodic symplectic maps via structure-preserving neural networks
Valentin Duruisseaux, Joshua W. Burby, Qi Tang
A continuous-time dynamical system with parameter is nearly-periodic if all its trajectories are periodic with nowhere-vanishing angular frequency as ap…
Practical Perspectives on Symplectic Accelerated Optimization
Valentin Duruisseaux, Melvin Leok
Geometric numerical integration has recently been exploited to design symplectic accelerated optimization algorithms by simulating the Lagrangian and Hamiltonian systems from the v…
Bistability, Bifurcations and Chaos in the Mackey-Glass Equation
Valentin Duruisseaux, Antony R. Humphries
Numerical bifurcation analysis, and in particular two-parameter continuation, is used in consort with numerical simulation to reveal complicated dynamics in the Mackey-Glass equati…
Accelerated Optimization on Riemannian Manifolds via Projected Variational Integrators
Valentin Duruisseaux, Melvin Leok
A variational formulation of accelerated optimization on normed spaces was recently introduced by considering a specific family of time-dependent Bregman Lagrangian and Hamiltonian…
Time-adaptive Lagrangian Variational Integrators for Accelerated Optimization on Manifolds
Valentin Duruisseaux, Melvin Leok
A variational framework for accelerated optimization was recently introduced on normed vector spaces and Riemannian manifolds in Wibisono et al. (2016) and Duruisseaux and Leok (20…