CVRPWrapper "depots [depots] points [points] demands [demands] capacity [capacity] output [sol]" vrplib CVRPBWrapper "depots [depots] points [points] demands [demands ...

Which learning goals must individual computational elements pursue to contribute to a network-level task solution? This local understanding is missing in both biological, but also artificial neural ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Experiments in the physical chemistry laboratory often require moderately complex ...

CIANNA is a general-purpose deep learning framework primarily developed and used for astronomical data analysis. Functionalities and optimizations are added based on relevance for astrophysical ...

Contagion dynamics are usually separated into two classes: simple contagion, used notably to describe the spread of infectious diseases, and complex contagion, mainly used to model the spread of ...

PyMC is a probabilistic programming library for Python that provides tools for constructing and fitting Bayesian models. It offers an intuitive, readable syntax that is close to the natural syntax ...

Physics-Informed Neural Networks (PINN) emerged as a powerful tool for solving scientific computing problems, ranging from the solution of Partial Differential Equations to data assimilation tasks.

Physics-Informed Neural Networks (PINN) are neural networks encoding the problem governing equations, such as Partial Differential Equations (PDE), as a part of the neural network. PINNs have emerged ...