activity
20072025
most citedAbsence of charge order in the dimerized κ-phase BEDT-TTF salts

102 citations · 286 across the 18 of their papers we have counts for

collaborators

19 papers

cond-mat.stat-mech2025★ 1 cited

Dreaming up scale invariance via inverse renormalization group

Adam Rançon, Ulysse Rançon, Tomislav Ivek +1

We explore how minimal neural networks can invert the renormalization group (RG) coarse-graining procedure in the two-dimensional Ising model, effectively ``dreaming up'' microscop…

cond-mat.str-el2022★ 5 cited

Spin-Reorientation-Driven Linear Magnetoelectric Effect in Topological Antiferromagnet CuTeO

Virna Kisiček, Damir Dominko, Matija Čulo +7

The search for new materials for energy-efficient electronic devices has gained unprecedented importance. Among the various classes of magnetic materials driving this search are an…

stat.ML2022

Reconstruction of Incomplete Wildfire Data using Deep Generative Models

Tomislav Ivek, Domagoj Vlah

We present our submission to the Extreme Value Analysis 2021 Data Challenge in which teams were asked to accurately predict distributions of wildfire frequency and size within spat…

cond-mat.str-el2021

Persisting correlation between electrical transport and magnetic dynamics in M-type hexaferrites

Željko Rapljenović, Nikolina Novosel, Damir Dominko +8

In this work we present frequency-dependent magnetic susceptibility and dc electric transport properties of three different compositions of hexaferrite BaPbFe$_{12-y}…

cond-mat.str-el2021★ 2 cited

Control of a polar order via magnetic field in a vector-chiral magnet

Martina Dragičević, David Rivas Góngora, Željko Rapljenović +8

Vector-chiral (VC) antiferromagnetism is a spiral-like ordering of spins which may allow ferroelectricity to occur due to loss of space inversion symmetry. In this paper we report…

cs.LG2020

BlackBox: Generalizable Reconstruction of Extremal Values from Incomplete Spatio-Temporal Data

Tomislav Ivek, Domagoj Vlah

We describe our submission to the Extreme Value Analysis 2019 Data Challenge in which teams were asked to predict extremes of sea surface temperature anomaly within spatio-temporal…