A central result in the foundations of quantum mechanics is the Kochen-Specker theorem. In
short, it states that quantum mechanics is in conflict with classical models in which the result …

With quantum computing technologies nearing the era of commercialization and quantum
supremacy, machine learning (ML) appears as one of the promising'killer'applications …

Inspired by the success of Boltzmann machines based on classical Boltzmann distribution,
we propose a new machine-learning approach based on quantum Boltzmann distribution of …

The field of classical stochastic processes forms a major branch of mathematics. Stochastic
processes are, of course, also very well studied in biology, chemistry, ecology, geology …

Quantum mechanics predicts that measurements of incompatible observables carry a
minimum uncertainty which is independent of technical deficiencies of the measurement …

Mainstream machine-learning techniques such as deep learning and probabilistic
programming rely heavily on sampling from generally intractable probability distributions …

This paper explores the use of applied mathematical modelling in the field of evolutionary
biochemistry. The authors demonstrate how mathematical models can be applied to better …

Nowadays there is solid clinical information for combining β 2-agonists and anti-muscarinic
agents, although the nature (additive or synergistic) of the net clinical result obtained by co …

The increasing impact of flooding urges more effective flood management strategies to
guarantee sustainable ecosystem development. Recent catastrophes underline the …

Non-Markovian quantum processes exhibit different memory effects when measured in
different ways; an unambiguous characterization of memory length requires accounting for …