3 citations · 3 across the 5 of their papers we have counts for
6 papers
Characterizing High-Capacity Janus Aminobenzene-Graphene Anode for Sodium-Ion Batteries with Machine Learning
Claudia Islas-Vargas, L. Ricardo Montoya, Carlos A. Vital-José +3
Sodium-ion batteries require anodes that combine high capacity, low operating voltage, fast Na-ion transport, and mechanical stability, which conventional anodes struggle to delive…
Noise & pattern: identity-anchored Tikhonov regularization for robust structural anomaly detection
Alexander Bauer, Klaus-Robert Müller
Anomaly detection plays a pivotal role in automated industrial inspection, aiming to identify subtle or rare defects in otherwise uniform visual patterns. As collecting representat…
Sampling 3D Molecular Conformers with Diffusion Transformers
J. Thorben Frank, Winfried Ripken, Gregor Lied +3
Diffusion Transformers (DiTs) have demonstrated strong performance in generative modeling, particularly in image synthesis, making them a compelling choice for molecular conformer…
Complete and Efficient Covariants for 3D Point Configurations with Application to Learning Molecular Quantum Properties
Hartmut Maennel, Oliver T. Unke, Klaus-Robert Müller
When modeling physical properties of molecules with machine learning, it is desirable to incorporate -covariance. While such models based on low body order features are not…
Aligning Machine and Human Visual Representations across Abstraction Levels
Lukas Muttenthaler, Klaus Greff, Frieda Born +6
Deep neural networks have achieved success across a wide range of applications, including as models of human behavior and neural representations in vision tasks. However, neural ne…
Automated Dissipation Control for Turbulence Simulation with Shell Models
Ann-Kathrin Dombrowski, Klaus-Robert Müller, Wolf Christian Müller
The application of machine learning (ML) techniques, especially neural networks, has seen tremendous success at processing images and language. This is because we often lack formal…