48 citations · 177 across the 8 of their papers we have counts for
12 papers
Probing optimisation in physics-informed neural networks
Nayara Fonseca, Veronica Guidetti, Will Trojak
A novel comparison is presented of the effect of optimiser choice on the accuracy of physics-informed neural networks (PINNs). To give insight into why some optimisers are better,…
Axionic Festina Lente
Veronica Guidetti, Nicole Righi, Victoria Venken +1
The swampland conjecture known as Festina Lente (FL) imposes a lower bound on the mass of all charged particles in a quasi-de Sitter space. In this paper, we propose the aFL (axion…
Generalizing similarity in noisy setups: the DIBS phenomenon
Nayara Fonseca, Veronica Guidetti
This work uncovers an interplay among data density, noise, and the generalization ability in similarity learning. We consider Siamese Neural Networks (SNNs), which are the basic fo…
Fuzzy Dark Matter Candidates from String Theory
Michele Cicoli, Veronica Guidetti, Nicole Righi +1
String theory has been claimed to give rise to natural fuzzy dark matter candidates in the form of ultralight axions. In this paper we revisit this claim by a detailed study of how…
A Fake Instability in String Inflation
Michele Cicoli, Veronica Guidetti, Francesco Muia +2
In type IIB Fibre Inflation models the inflaton is a Kaehler modulus which is kinetically coupled to the corresponding axion. In this setup the curvature of the field space induces…
On the choice of entropy variables in multifield inflation
Michele Cicoli, Veronica Guidetti, Francesco Muia +2
We discuss the usefulness and theoretical consistency of different entropy variables used in the literature to describe isocurvature perturbations in multifield inflationary models…