The aim of this course is to provide an introduction to modern methods for studying nonlinear partial differential equations. The content of the course, which can change from time to time, is built ...

The aim of this course is to provide an introduction to modern methods for studying nonlinear partial differential equations. The content of the course, which can change from time to time, is built ...

py-pde is a Python package for solving partial differential equations (PDEs). The package provides classes for grids on which scalar and tensor fields can be defined. The associated differential ...

Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods ...

The HGF is a recent derivation of one-step update equations from Bayesian principles that rests on a hierarchical generative ... choice of decision model affects which HGF parameters can be estimated.

In order to reduce the computational burden of GD for the optimization process (7), we propose a modification of this algorithm which includes the aforementioned RBM for the numerical simulation of ...

Max-Planck-Institut für Kohlenforschung, Mülheim an der Ruhr 45470, Germany ...