Gradient Descent Optimizers and Genetic Algorithms using GPUs, CPUs, and FPGAs via CUDA, OpenCL, and oneAPI
Classes enabling finmath-lib to run its Monte-Carlo models on Cuda GPUs
A simple yet sufficiently fast (attenuated) Radon and backproject implementation using KernelAbstractions
GPU-accelerated Marginalized Graph Kernel with customizable node and edge features; Gaussian process regression