activity
20242026
collaborators

7 papers

cs.LG2026

Learning functional components of PDEs from data using neural networks

Torkel E. Loman, Yurij Salmaniw, Antonio Leon Villares +2

Partial differential equations often contain unknown functions that are difficult or impossible to measure directly, hampering our ability to derive predictions from the model. Wor…

math.NA2026

Numerical stationary states for nonlocal Fokker-Planck equations via fixed points of consistency maps

José A. Carrillo, Yurij Salmaniw, Antonio León Villares

We propose a fixed-point-based numerical framework for computing stationary states of nonlocal Fokker-Planck-type equations. Instead of discretising the differential operators dire…

math.AP2025

Long-time behaviour and bifurcation analysis of a two-species aggregation-diffusion system on the torus

José A. Carrillo, Yurij Salmaniw

We investigate stationary states, including their existence and stability, in a class of nonlocal aggregation-diffusion equations with linear diffusion and symmetric nonlocal inter…

math.AP2025

Well-posedness of aggregation-diffusion systems with irregular kernels

José A. Carrillo, Yurij Salmaniw, Jakub Skrzeczkowski

We consider aggregation-diffusion equations with merely bounded nonlocal interaction potential . We are interested in establishing their well-posedness theory when the nonlocal…

math.AP2025

Structural identifiability of linear-in-parameter parabolic PDEs through auxiliary elliptic operators

Yurij Salmaniw, Alexander P Browning

Parameter identifiability is often requisite to the effective application of mathematical models in the interpretation of biological data, however theory applicable to the study of…

math.AP2025

Dynamics of a coupled nonlocal PDE-ODE system with spatial memory: well-posedness, stability, and bifurcation analysis

Yurij Salmaniw, Di Liu, Junping Shi +1

Nonlocal aggregation-diffusion models, when coupled with a spatial map, can capture cognitive and memory-based influences on animal movement and population-level patterns. In this…