activity
20172025
most citedDomain-adversarial neural networks to address the appearance variability of histopathology images

1.1k citations · 1.2k across the 4 of their papers we have counts for

collaborators

5 papers

cond-mat.dis-nn2025

Uncertainty Quantification in Multiscale Modeling of Polymer Composite Materials Using Physically Recurrent Neural Networks

N. Kovács, I. B. C. M. Rocha, F. P. van der Meer +2

This study investigates whether Physically Recurrent Neural Networks (PRNNs), a recent surrogate model for heterogeneous materials, trained on a micromodel with fixed material para…

astro-ph.SR202315 cited

VLTI/GRAVITY Observations and Characterization of the Brown Dwarf Companion HD 72946 B

W. O. Balmer, L. Pueyo, T. Stolker +96

Tension remains between the observed and modeled properties of substellar objects, but objects in binary orbits, with known dynamical masses can provide a way forward. HD 72946 B i…

astro-ph.SR202142 cited

A measure of the size of the magnetospheric accretion region in TW Hydrae

R. Garcia Lopez, A. Natta, A. Caratti o Garatti +69

Stars form by accreting material from their surrounding disks. There is a consensus that matter flowing through the disk is channelled onto the stellar surface by the stellar magne…

astro-ph.GA2018

A headless tadpole galaxy: the high gas-phase metallicity of the ultra-diffuse galaxy UGC 2162

J. Sanchez Almeida, A. Olmo-Garcia, B. G. Elmegreen +5

The cosmological numerical simulations tell us that accretion of external metal-poor gas drives star-formation (SF) in galaxy disks. One the best pieces of observational evidence s…

cs.CV20171.1k cited

Domain-adversarial neural networks to address the appearance variability of histopathology images

Maxime W. Lafarge, Josien P. W. Pluim, Koen A. J. Eppenhof +2

Preparing and scanning histopathology slides consists of several steps, each with a multitude of parameters. The parameters can vary between pathology labs and within the same lab…