7 papers
The Right Space for Dynamics: Numerics with Diffeomorphism Equivariance
Wolf-Juergen Beyn, Michail E. Kavousanakis, Yannis G. Kevrekidis
Among many (equivalent, via invertible transformations) representations of the evolution of a dynamical system, which one is to be preferred? Here we show how the use of infinite-d…
Conformal Disentanglement and Latent-Space Curation: A Neural Framework for Perspective Synthesis, Differentiation and Targeted Generation
George A. Kevrekidis, Eleni D. Koronaki, Dimitris G. Giovanis +1
Many scientific and engineering problems involve observing a common phenomenon through multiple heterogeneous sensors or measurement modalities. Such observations typically contain…
The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS)
Andrew Ferguson, Marisa LaFleur, Lars Ruthotto +97
This community paper developed out of the NSF Workshop on the Future of Artificial Intelligence (AI) and the Mathematical and Physics Sciences (MPS), which was held in March 2025 w…
A simulation that recapitulates the dynamics of PER-directed colloidal assembly
Cheng-Hung Chou, Pepijn G. Moerman, Sikao Guo +4
The self-assembly of DNA-coated colloids controlled by enzymatic reactions has the potential to enable the formation of materials with hierarchical organization and switchable conf…
Towards Coordinate- and Dimension-Agnostic Machine Learning for Partial Differential Equations
Trung V. Phan, George A. Kevrekidis, Soledad Villar +2
The machine learning methods for data-driven identification of partial differential equations (PDEs) are typically defined for a given number of spatial dimensions and a choice of…
Thinner Latent Spaces: Detecting Dimension and Imposing Invariance with Conformal Autoencoders
George A. Kevrekidis, Zan Ahmad, Mauro Maggioni +2
Conformal Autoencoders are a neural network architecture that imposes orthogonality conditions between the gradients of latent variables to obtain disentangled representations of d…