
Neural Ordinary Differential Equations
Introduces ODE-Nets, a continuous-depth neural network model parameterized by ODEs, enabling constant memory …

Introduces ODE-Nets, a continuous-depth neural network model parameterized by ODEs, enabling constant memory …

Flow matching model that co-generates ligands and flexible protein pockets, addressing rigid-receptor limitations in …

A Riemannian flow matching framework for generating Metal-Organic Framework structures by treating building blocks as …

Landmark numerical study revealing chaotic dynamics and unpredictability in planetary orbits using symplectic …

Application of dynamical corrections formalism to TST for LJ surface diffusion, revealing bounce-back recrossings at low …

Comprehensive user guide for the Embedded-Atom Method (EAM), covering theory, potential fitting, and applications to …

Comprehensive 1993 review of the Embedded-Atom Method (EAM), covering theory, parameterization, and applications to …

Foundational paper establishing the energy landscape theory, folding funnels, and the principle of minimal frustration.

Theoretical model using coupled differential equations to explain CO oxidation oscillations via surface phase …

Molecular dynamics simulation of Iridium surface diffusion confirming atomic exchange mechanisms using EAM and many-body …

A seminal kinetic model using coupled ODEs to explain temporal self-organization and mixed-mode oscillations on platinum …

In situ XRD validation of the oxide model driving kinetic rate oscillations in high-pressure CO oxidation on supported …