The rapid growth of large-scale neuroscience datasets has spurred diverse modeling strategies, ranging from mechanistic models grounded in biophysics, to phenomenological descriptions of neural ...

Abstract: This paper focuses on representation learning for dynamic graphs with temporal interactions. A fundamental issue is that both the graph structure and the nodes own their own dynamics, and ...

The well-optimized DifferentialEquations solvers benchmark as some of the fastest implementations of classic algorithms. It also includes algorithms from recent research which routinely outperform the ...

Authors may consider their applications in all branches of science and engineering, an analysis of their properties or derivations of numerical methods to solve them. Differential equations play a ...

A new editorial was published in Oncotarget, titled "Beyond pixels: Graph filtration learning unveils new dimensions in hepatocellular carcinoma imaging." As traditional pixel-based methods reach ...

ABSTRACT: This study compares the Adomian Decomposition Method (ADM) and the Variational Iteration Method (VIM) for solving nonlinear differential equations in engineering. Differential equations are ...

Now, when you want to solve a math equation and write it down, the Ink math assistant will jump into action and quickly plot an interactive graph to help you visualize those hard-to-understand math ...