output
19932026
most citedSchNet - a deep learning architecture for molecules and materials

2.3k citations

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142 papers · 1 filter

cond-mat.mes-hall2023★ 3 cited

Optimal half-metal band structure for large thermoelectric performance

Finantius E. M. Rahangiar, Adam B. Cahaya, Melania S. Muntini +2

Half-metal ferromagnets were predicted [in IEEE Trans. Mag. 51, 1 (2015)] to give large thermoelectric performance in anti-parallel spin valve configuration. Despite being metals t…

math.PR2023

Length spectrum of large genus random metric maps

Simon Barazer, Alessandro Giacchetto, Mingkun Liu

We study the length of short cycles on uniformly random metric maps (also known as ribbon graphs) of large genus using a Teichmüller theory approach. We establish that, as the genu…

cs.SE2023

Learning-Based Relaxation of Completeness Requirements for Data Entry Forms

Hichem Belgacem, Xiaochen Li, Domenico Bianculli +1

Data entry forms use completeness requirements to specify the fields that are required or optional to fill for collecting necessary information from different types of users. Howev…

cs.LO2023★ 1 cited

An Encoding of Abstract Dialectical Frameworks into Higher-Order Logic

Antoine Martina, Alexander Steen

An approach for encoding abstract dialectical frameworks and their semantics into classical higher-order logic is presented. Important properties and semantic relationships are for…

math.AG2023★ 1 cited

Vector fields and admissible embeddings for quiver moduli

Pieter Belmans, Ana-Maria Brecan, Hans Franzen +1

We introduce a double framing construction for moduli spaces of quiver representations. It allows us to reduce certain sheaf cohomology computations involving the universal represe…

cs.RO2023★ 16 cited

GraspLDM: Generative 6-DoF Grasp Synthesis using Latent Diffusion Models

Kuldeep R Barad, Andrej Orsula, Antoine Richard +3

Vision-based grasping of unknown objects in unstructured environments is a key challenge for autonomous robotic manipulation. A practical grasp synthesis system is required to gene…