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Elasto-plastic boundary value problems in geotechnical engineering are conventionally solved by the Finite Element Method (FEM), which incurs high computational cost from incremental-iterative procedures. Physics-Informed Neural Networks…
We study traveling waves in a class of high-dimensional plant-consumer reaction-diffusion systems with $N$ competing plant species and $N$ associated consumer populations. The consumer equations are linearly degenerate at the extinction…
Deep learning surrogate models trained with mean-squared-error loss produce statistically accurate but physically unconstrained flood predictions: water may flow uphill, appear spontaneously, or smooth over street-level corridors. We…
Trajectory data collected in real-world settings is frequently incomplete due to sensor failure, communication loss, or occlusion. We address the task of \emph{trajectory inpainting}: reconstructing contiguous missing segments from observed…
The distance between persons reveals significant information about their perception of each other. However, such information is not easily extractable and interpretable from video input. We developed an open-sourced library, Facial…
We implement an agentic AI workflow built around a large language model (LLM) agent for autonomous experiments with nitrogen-vacancy (NV) centers in diamond. NV centers are a widely used platform for quantum sensing, and the ability to…
This study presents a theoretical analysis of partitional clustering on networks, analyzing both hard and soft assignment schemes with different objective functions. Cluster centers are not restricted to vertices but can also be located…
This paper assesses the readiness of T\"urkiye's electric vehicle (EV) charging infrastructure to support cost-competitive intercity travel compared to internal combustion engine (ICE) vehicles. Utilizing a directed acyclic graph-based…
Multiscale problems with evolving interfaces are ubiquitous in science and engineering. Phase-field models are a powerful tool for simulating interface-dominated phenomena in computational mechanics and materials modeling, but their…
Large Language Models (LLMs) are increasingly used to generate executable software environments from repository artifacts. However, functional executability does not necessarily imply conformity with architectural, security, workflow, and…
This paper studies the behavior of language models in a multi-agent crowd simulation, focusing on how affect propagates among agents that perceive and appraise one another. Each agent perceives its neighbors through visual, auditory, and…
Simple and complex contagions differ mechanistically; multiple exposures act synergistically in the latter but independently in the former. Yet correlated mixtures of simple contagions may appear complex when inferring global contagion…
Safety inflation can cause nearby obstacles to overlap, violating the disjoint-obstacle assumptions used by many modulation-based reactive planners. We investigate Star-World workspace reshaping for three-dimensional reactive control of a…
We discuss two-point functions and the energy momentum tensor of the classical gluon field after the collision of sheets of color charges on the light cone in the weak-field limit. The classical fields created by such a setup is thought to…
Research on preference optimization often varies the training objective while holding the data fixed. We instead ask whether a small, high-confidence set of on-policy responses can provide a reliable learning signal. Our method, DMAPO…
Recent advances in RAG aim to optimize for performance by paying high ingestion costs for knowledge ingestion: building knowledge graphs or extracting SQL tables. In this work we show that the operations that such knowledge bases allow can…
Matrices and involutions in/on the algebras $B(\mathbb{R})$ and $B(\mathbb{C})$ of real (resp., complex) row- and column-finite $\omega\times\omega$ matrices are studied. It is proved that any positive definite $\mathbb{R}$-algebra…
We develop a geometric--spectral framework for the computation and stability analysis of quasi-normal modes (QNMs) in open optical cavities of compact support. The hyperboloidal approach, transferred from gravitational physics to…
A central challenge in interpreting learned decision-making systems is to determine whether their internal representations contain concepts that help explain their behavior. We report interpretability experiments for a tokenized…
Empirical user studies are essential for evaluating visual encodings and can reveal perceptual and cognitive mechanisms, but they do not by themselves provide causal, predictive accounts of interpretation errors. Evaluations are therefore…