It can take years for humans to solve complex scientific problems. With AI, it can take a fraction of the time.

Probability and Statistics Group research at the School of Mathematical and Computer Sciences at Heriot-Watt University, Edinburgh.

Keywords: nonlinear and linear PDEs, Kimura model, functional-differential variational inequalities, transmission problem, Caputo derivatives, stochastic PDEs, extremal problem of approximation theory ...

By implementing non-linear interpolations, including polynomial or spline methods, it is possible to refine the shape of the characteristic curves in such a way that energy loss estimation is more ...

However, in existing works, the log-linear models are all derived based on first-order linearization approximation, which seemingly goes against their successful applications in INS initial alignment ...

We apply a self-consistent relativistic mean-field variational ``Gaussian functional'' (or Hartree) approximation to the linear \sigma σ model with spontaneously and explicitly broken chiral O (4) ...

ˆμP is 1 if the load consumes constant power; 0 otherwise. Linear Approximations Equation (4) and the third term in (5) are nonlinear due to the term 1 / V . In [10] is presented the following ...

In both linear and nonlinear chromatography, the lumped kinetic model is a suitable model for predicting elution bands when appropriate equilibrium functions and mass transfer coefficients are ...

PiecewiseLinApprox.jl (formerly LinA.jl) is a state-of-the-art piecewise linear approximation package that approximates (or over/under-estimates) univariate differentiable $\mathbb{R} \rightarrow ...