9 citations
6 papers
Bayesian Latent Space Models for Graphs Are Misspecified: Toward Robust Inference via Generalized Posteriors
Aldric Labarthe
Bayesian latent space models offer a principled approach to network representation, but rely on correct specification of both geometry and link function. Real-world networks often…
Aligning the Unseen in Attributed Graphs: Interplay between Graph Geometry and Node Attributes Manifold
Aldric Labarthe, Roland Bouffanais, Julien Randon-Furling
The standard approach to representation learning on attributed graphs -- i.e., simultaneously reconstructing node attributes and graph structure -- is geometrically flawed, as it m…
Superconductivity near Pomeranchuk instabilities in the spin channel
Daniel G. Barci, Paulo S. A. Bonfim
We study the competition between a Pomeranchuk instability in the spin channel with angular momentum and an attractive interaction, favoring Cooper-pair formation. We foun…
School evasion: A hard reality
V. L. L. S. Pinto, F. A. O. Cruz
The present work has as objective to show the profile of students who abandoned the studies in a High School, located in Sao Joao de Meriti city, municipal district of Rio de Janei…
Solution Poisson-Boltzmann equation: Application in the Human Neuron Membrane
M. A. G. Soares, F. A. O. Cruz, C. M. Cortez
With already demonstrated in previous work the equations that describe the space dependence of the electric potential are determined by the solution of the equation of Poisson-Bolt…
On the BFFT quantization of first order systems
Ricardo Amorim, Ronaldo Thibes
By using the field-antifield formalism, we show that the method of Batalin, Fradkin, Fradkina and Tyutin to convert Hamiltonian systems submitted to second class constraints introd…