Full-waveform inversion (FWI) is a popularly used high-resolution seismic inversion method.
It relies on the measure of the misfit between observed data and predicted data. Due to the …

We develop a compositional approach for automatic and symbolic differentiation based on
categorical constructions in functional analysis where derivatives are linear functions on …

Continuum-kinematics-inspired peridynamics (CPD) has been recently proposed as a novel
reformulation of peridynamics that is characterized by one-, two-and three-neighbor …

Both forward and reverse mode automatic differentiation derive a model function as used for
gradient descent automatically. Reverse mode calculates all derivatives in one run, whereas …

Satellite aerosol optical depth (AOD) plays an important role for high spatiotemporal-
resolution estimation of fine particulate matter with diameters≤ 2.5 μm (PM2. 5). However …

Computational techniques allow breaking the limits of traditional imaging methods, such as
time restrictions, resolution, and optics flaws. While simple computational methods can be …

Cette thèse de doctorat présente trois contributions dans le domaine de la programmation
différentiable axée sur les données relationnelles. Les données relationnelles sont …

Kotlin is a statically-typed programming language with support for embedded domain
specific languages, asynchronous programming, and multi-platform compilation. In this …

This paper presents a novel optimization for differentiable programming named coarsening
optimization. It offers a systematic way to synergize symbolic differentiation and algorithmic …

We have built a Shallow Gibbs Network model as a Random Gibbs Network Forest to reach
the performance of the Multilayer feedforward Neural Network in a few numbers of …