This is a preview. Log in through your library . Abstract Under general assumptions we give upper bounds, proportional to the volume of the domain, on the temporal and spatial complexity of solutions ...

We consider the problem of numerically estimating expectations of solutions to stochastic differential equations driven by Brownian motions in the commonly occurring small noise regime. We consider (i ...

In this Artificial Intelligence podcast with Lex Fridman, computer scientist Donald Knuth discusses Alan Turing, Neural networks, machine learning and other AI topics from ant colonies and human ...

Most mathematical models do not admit exact solutions. Asymptotic and perturbation methods provide powerful techniques for obtaining approximate solutions, which allow one to draw physical conclusions ...

Abelian complexity offers a nuanced quantification of the diversity in words by considering the frequency of symbols rather than their order. At its core, it examines the number of distinct Parikh ...