A Cross-Platform Collection of Social Network Profiles. - Maria Han Veiga; Carsten Eickhoff (SIGIR, 2016)

Privacy Leakage through Innocent Content Sharing in Online Social Networks. - Maria Han Veiga; Carsten Eickhoff (CoRR, 2016)

Capturing near-equilibrium solutions: a comparison between high-order Discontinuous Galerkin methods and well-balanced schemes. - Maria Han Veiga; Rémi Abgrall; Romain Teyssier (CoRR, 2018)

What Do Language Representations Really Represent? - Johannes Bjerva; Robert Östling; Maria Han Veiga; Jörg Tiedemann; Isabelle Augenstein (Comput. Linguistics, 2019)

Neural network based limiter with transfer learning. - Maria Han Veiga; Rémi Abgrall (CoRR, 2019)

DeC and ADER: Similarities, Differences and an Unified Framework. - Maria Han Veiga; Philipp Öffner; Davide Torlo (CoRR, 2020)

Reconstruction of the Density Power Spectrum from Quasar Spectra using Machine Learning. - Maria Han Veiga; Xi Meng; Oleg Y. Gnedin; Nickolay Y. Gnedin; Xun Huan (CoRR, 2021)

An arbitrary high-order Spectral Difference method for the induction equation. - Maria Han Veiga; David A. Velasco-Romero; Quentin Wenger; Romain Teyssier (J. Comput. Phys., 2021)

DeC and ADER: Similarities, Differences and a Unified Framework. - Maria Han Veiga; Philipp Öffner; Davide Torlo (J. Sci. Comput., 2021)

A new variable shape parameter strategy for RBF approximation using neural networks. - Fatemeh Nassajian Mojarrad; Maria Han Veiga; Jan S. Hesthaven; Philipp Öffner (Comput. Math. Appl., 2023)

Matryoshka Policy Gradient for Entropy-Regularized RL: Convergence and Global Optimality. - François Ged; Maria Han Veiga (CoRR, 2023)

An Interdisciplinary Outlook on Large Language Models for Scientific Research. - James Boyko; Joseph Cohen; Nathan Fox; Maria Han Veiga; Jennifer I-Hsiu Li; Jing Liu; Bernardo Modenesi; Andreas H. Rauch; Kenneth N. Reid; Soumi Tribedi; Anastasia Visheratina; Xin Xie (CoRR, 2023)

Learning a robust shape parameter for RBF approximation. - Maria Han Veiga; Fatemeh Nassajian Mojarrad (CoRR, 2024)

On improving the efficiency of ADER methods. - Maria Han Veiga; Lorenzo Micalizzi; Davide Torlo (Appl. Math. Comput., 2024)

Kernel-Smoothed Scores for Denoising Diffusion: A Bias-Variance Study. - Franck Gabriel; François Ged; Maria Han Veiga; Emmanuel Schertzer (CoRR, 2025)