Lax dynamics
A novel approach is proposed to characterize the dynamics of perturbed many-body integrable systems. Focusing on the paradigmatic case of the Toda chain under non-integrable Hamiltonian perturbations, this study introduces a method based the time evolution of the Lax eigenvalues $\lambda_\alpha$ as...
ScaleGNN: Towards Scalable Graph Neural Networks via Adaptive High-order Neighboring Feature Fusion
Graph Neural Networks (GNNs) have demonstrated strong performance across various graph-based tasks by effectively capturing relational information between nodes. These models rely on iterative message passing to propagate node features, enabling nodes to aggregate information from their neighbors. Recent research has significantly...
Improving robustness and training efficiency of machine-learned potentials by incorporating short-range empirical potentials
Machine learning force fields (MLFFs) are powerful tools for materials modeling, but their performance is often limited by training dataset quality, particularly the lack of rare event configurations. This limitation undermines their accuracy and robustness in long-time and large-scale molecular dynamics simulations....
StreamRL: Scalable, Heterogeneous, and Elastic RL for LLMs with Disaggregated Stream Generation
Reinforcement learning (RL) has become the core post-training technique for large language models (LLMs). RL for LLMs involves two stages: generation and training. The LLM first generates samples online, which are then used to derive rewards for training. The conventional view holds...
Benchmarking der Reproduzierbarkeit der MRT-Segmentierung des Gehirns übergreifend Scanner und Zeit
Accurate and reproducible brain morphometry from structural MRI is critical for monitoring neuroanatomical changes across time and across imaging domains. Although deep learning has accelerated segmentation workflows, scanner-induced variability and reproducibility limitations remain-especially in longitudinal and multi-site settings. In dieser Studie, Wir...
Echtzeit-Rohsignal-Genomanalyse mit vollständig integriertem Memristor Hardware
Advances in third-generation sequencing have enabled portable and real-time genomic sequencing, Die Datenverarbeitung in Echtzeit bleibt jedoch ein Engpass, Dies erschwert die Genomanalyse vor Ort aufgrund unerschwinglicher Zeit- und Energiekosten. These technologies generate a massive amount of noisy analog signals that traditionally require...
Zwischenmodulare Kurven mit unendlich vielen Quartic-Punkten
Für jede Gruppe $\{\pm1\}\subseteq \Delta\subseteq (\mathbb Z/N\mathbb Z)^\times$, there exists an intermediate modular curve $X_\Delta(N)$. In this paper we determine all curves $X_\Delta(N)$ with infinitely many points of degree $4$ over $\mathbb Q$. Um das zu tun, we developed a method to compute...
Widersprüchliche Beobachtungen in der Wettervorhersage
AI-based systems, such as Google’s GenCast, have recently redefined the state of the art in weather forecasting, offering more accurate and timely predictions of both everyday weather and extreme events. While these systems are on the verge of replacing traditional meteorological methods,...
Understanding the Role of Covariates in Numerical Reconstructions of Real-World Vehicle-to-Pedestrian Collisions
Traumatic Brain Injuries (TBIs) are a pressing global public health issue, impacting tens of millions of individuals annually. Vulnerable road users (VRUs), such as pedestrians, are vastly overrepresented in the worldwide TBI statistics. To evaluate the effectiveness of injury prevention measures, researchers...
Rekonstruktion des dreidimensionalen Flüssigkeitsspannungsfeldes über Photoelastizität unter Verwendung eines physikinformierten Faltungs-Encoder-Decoders
Measuring stress fields in fluids and soft materials is crucial in various fields such as mechanical engineering, medicine, and bioengineering. Jedoch, conventional methods that calculate stress fields from velocity fields struggle to measure complex fluids where the stress constitutive equation is unknown....