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20192026
most citedElectron-Electron Interactions in Device Simulation via Non-equilibrium Green's Functions and the GW Approximation

6 citations · 33 across the 24 of their papers we have counts for

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Showing 2025Show all

6 papers · 1 filter

stat.CO2025

Accelerated Spatio-Temporal Bayesian Modeling for Multivariate Gaussian Processes

Lisa Gaedke-Merzhäuser, Vincent Maillou, Fernando Rodriguez Avellaneda +5

Multivariate Gaussian processes (GPs) offer a powerful probabilistic framework to represent complex interdependent phenomena. They pose, however, significant computational challeng…

cs.DC2025

Ab-initio Quantum Transport with the GW Approximation, 42,240 Atoms, and Sustained Exascale Performance

Nicolas Vetsch, Alexander Maeder, Vincent Maillou +7

Designing nanoscale electronic devices such as the currently manufactured nanoribbon field-effect transistors (NRFETs) requires advanced modeling tools capturing all relevant quant…

cs.LG2025

Distributed Equivariant Graph Neural Networks for Large-Scale Electronic Structure Prediction

Manasa Kaniselvan, Alexander Maeder, Chen Hao Xia +2

Equivariant Graph Neural Networks (eGNNs) trained on density-functional theory (DFT) data can potentially perform electronic structure prediction at unprecedented scales, enabling…

cs.PL2025

Comparing Parallel Functional Array Languages: Programming and Performance

David van Balen, Tiziano De Matteis, Clemens Grelck +12

Parallel functional array languages are an emerging class of programming languages that promise to combine low-effort parallel programming with good performance and performance por…

cs.DC2025★ 2 cited

Serinv: A Scalable Library for the Selected Inversion of Block-Tridiagonal with Arrowhead Matrices

Vincent Maillou, Lisa Gaedke-Merzhaeuser, Alexandros Nikolaos Ziogas +2

The inversion of structured sparse matrices is a key but computationally and memory-intensive operation in many scientific applications. There are cases, however, where only partic…

cond-mat.mtrl-sci2025

Learning the Electronic Hamiltonian of Large Atomic Structures

Chen Hao Xia, Manasa Kaniselvan, Alexandros Nikolaos Ziogas +4

Graph neural networks (GNNs) have shown promise in learning the ground-state electronic properties of materials, subverting ab initio density functional theory (DFT) calculations w…