Stochastic Gradient MCMC for Large-Scale Gaussian Process Spatial Modeling | HackerNoon
Gaussian processes (GPs) face challenges in scalability due to cubic time complexity in spatial datasets. Our SGMCMC framework provides a solution for efficient computation.
Your next gaming dice could be shaped like a dragon or armadillo
"The real behavior of a rolling object is largely a function of its geometry. This insight is essential for accurately predicting how rigid bodies will behave in various contexts."
NonlinearSolve.jl: Other References You Can Turn to | HackerNoon
NonlinearSolve.jl demonstrates advanced capabilities for solving nonlinear systems, showcasing features like a unified API, automatic algorithm selection, and non-allocating kernels, enhancing performance.