A novel hybrid framework for efficient higher order ODE solvers using neural networks and block methods. [PDF]
Sci RepMurugesh V +7 more
europepmc +1 more source
Accurate and Efficient Data‐Driven Partitioned Scheme for Coupled Heterogeneous Numerical Models
Numerical Methods for Partial Differential Equations, Volume 42, Issue 5, September 2026.ABSTRACT Heterogeneous numerical models (HNMs) combine conventional discretization modules such as finite elements with nonconventional data‐driven and reduced‐order modules. HNMs can improve computational efficiency and enable simulations of multi‐physics systems in which one or more constituent components lack first‐principles descriptions and must ...
Edward Huynh +3 more
wiley +1 more source
Invertible liquid neural network-based learning of inverse kinematics and dynamics for robotic manipulators. [PDF]
Sci RepZhang Y +8 more
europepmc +1 more source
Numerical Methods for Partial Differential Equations, Volume 42, Issue 5, September 2026.ABSTRACT In this paper we study the long‐time stability of the Cauchy one‐leg θ$$ \theta $$‐methods for the two‐dimensional Navier‐Stokes equations. We establish the uniform dissipativity in H1$$ {H}^1 $$, in the sense that the semi‐discrete‐in‐time approximations possess a global attractor for a small enough time step, using the discrete Grönwall ...
Isabel Barrio Sanchez +2 more
wiley +1 more source
Research on the Stability Model in Discrete Dynamical Systems with the Lorenz Attractor and the Kropotov-Pakhomov Neural Network. [PDF]
Entropy (Basel)Gospodinova EA.
europepmc +1 more source
Model Predictive Control of Gas Networks Based on Port‐Hamiltonian Formulations
Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 3, September 2026.ABSTRACT To efficiently compute optimal compressor actions in gas networks, we investigate port‐Hamiltonian models consisting of linear and a nonlinear model assumptions. The control actions are derived via adjoint‐based gradients that incorporate the constraints of the underlying optimization problem. We then present results from the implementation of
Andres Ortegón‐Villacorte +1 more
wiley +1 more source
Privacy-Preserving Head Pose Estimation System for Measuring Cervical Range of Motion. [PDF]
Sensors (Basel)Liu Z, Zhang L, Li G, McCarthy PW.
europepmc +1 more source
Learning Differential Equations From Numerically Integrated Artificial Neural Networks
Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 3, September 2026.ABSTRACT For numerical investigation of dynamical systems, the formulation of the corresponding ordinary differential equations (ODE) based on physical principles is usually the first and most crucial step. However, if the underlying physics is not fully understood or the required expert knowledge for modeling is missing, setting up these differential ...
Timo Bielitz, Dieter Bestle
wiley +1 more source
Convergence Guarantees for Time-Inhomogeneous Uniform-Rate Discrete Diffusion Models. [PDF]
Entropy (Basel)Liang Y, Lai L, Shroff N, Liang Y.
europepmc +1 more source
Redefining Optimal Coverage Path Planning for FLS‐Equipped AUVs With Deep Reinforcement Learning
Journal of Field Robotics, Volume 43, Issue 6, Page 3617-3632, September 2026.ABSTRACT Autonomous Underwater Vehicles (AUVs) have emerged as indispensable tools for a variety of subsea tasks, from habitat monitoring and seabed mapping to infrastructure inspection and mine countermeasures. A fundamental challenge in this field is Coverage Path Planning (CPP), the problem of ensuring complete and efficient area coverage.
Lorenzo Cecchi +3 more
wiley +1 more source