These are my go-to libraries for Python data crunching.

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Programming is a key transferable skill within the chemical sciences with applications ...

The Simulated Bifurcation (SB) algorithm is a fast and highly parallelizable state-of-the-art algorithm for quadratic combinatorial optimization inspired by quantum physics and spins dynamics. It ...

GUNNS is a set of generic C++ math models that combines nodal circuit analysis algorithms with the hydraulic-thermal-electric analogy to model flow circuits (fluid, thermal, electrical). The models ...

The German historian Oswald Spengler considered our age the age of abstraction. Nowhere is this more apparent than in programming, where abstraction isn’t just a conceptual convenience but an absolute ...

We present three possible strategies to effectively incorporate geological and/or geophysical constraints into deep neural networks (DNNs). They help address the main challenges of poor ...

GPUs have become a household name in High Performance Computing (HPC) systems over the last 15 years. However, programming GPUs is still largely a manual and arduous task, which requires expert ...

We demonstrate that a neural network automatically solves, explains, and generates university-level problems from the largest Massachusetts Institute of Technology (MIT) mathematics courses at a human ...

Physical scientists and engineering research and development (R&D) teams are embracing neural networks in attempts to accelerate their simulations. From quantum mechanics to the prediction of blood ...

The control of general nonlinear systems is a challenging task in particular for large-scale models as they occur in the semi-discretization of partial differential equations (PDEs) of, say, fluid ...