Collection of notebooks about quantitative finance, with interactive python code.
Learning in infinite dimension with neural operators.
Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
Next generation FEniCS problem solving environment for solving finite element problems
FreeFEM source code
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
Grid-based approximation of partial differential equations in Julia
Simulation and Parameter Estimation in Geophysics - A python package for simulation and gradient based parameter estimation in the context of geophysical applications.
FiPy is a Finite Volume PDE solver written in Python
Julia package for function approximation