Measurements of shear wave velocity (Vs) with uncertainty are critical for site-specific probabilistic seismic hazard studies. However, rigorously quantifying the uncertainty in Vs over large enough a...
Anti-inflammatory agents are critical for managing chronic conditions, yet traditional non-selective inhibitors often lead to severe gastrointestinal or cardiovascular events. This study presents an i...
Mesophotic coral ecosystems (MCEs; ∼30 to 150 meters) are major but poorly understood benthic habitats. We used Autonomous Reef Monitoring Structures (ARMS) and integrated metabarcoding (mtCOI and 18S...
Paint-derived particles are increasingly recognised as a major contributor to marine microplastic pollution, yet emissions from active vessels under routine operational conditions remain poorly charac...
Summary: Dynamic scientific machine learning (SciML) models that combine mechanistic ordinary differential equations (ODEs) with machine learning (ML) components have applications ranging from learnin...
Deep learning models often struggle under natural distribution shifts, a common challenge in real-world deployments. Test-Time Adaptation (TTA) addresses this by adapting models during inference witho...
We study mean estimation for a Gaussian distribution with identity covariance in $\mathbb{R}^d$ under a missing data scheme termed realizable $ε$-contamination model. In this model an adversary can ch...
We study outlier tokens in Diffusion Transformers (DiTs) for image generation. Prior work has shown that Vision Transformers (ViTs) can produce a small number of high-norm tokens that attract dispropo...
Reinforcement Learning (RL) with rubric-based rewards has recently shown remarkable progress in enhancing general reasoning capabilities of Large Language Models (LLMs), yet still suffers from ineffec...
We study the minimax risk for detecting a sparse elevated-mean Gaussian submatrix inside a larger noisy matrix. When the planted submatrix has size $n\times n$ and the ambient matrix has size $N\times...
Bitcoin inverse options, traded on the Deribit exchange and settled in the underlying cryptocurrency rather than in fiat currency, combine extreme and genuinely rough volatility dynamics with a non-li...
High-dimensional biomedical studies require models that are simultaneously accurate, sparse, and interpretable, yet exact best subset selection for generalized linear models is computationally intract...
Over the past two decades, millions of hectares of land in Africa have been transferred to investors, raising fears of displacement and conflict. This paper estimates the causal impact of large-scale ...
How level-0 players behave and how they are perceived by higher-level players are central questions in the literature on level-k models of boundedly rational strategic reasoning. To study these twin q...
As AI writing assistants become increasingly integrated into real-world drafting and revision workflows, many documents are no longer purely human-written or AI-generated, but instead result from prog...
Agents now write knowledge graphs, but knowledge-graph stores still carry defaults set when humans curated them: accept writes now and clean later, keep one time axis or none, treat every writer's fac...
Causal discovery algorithms learn a network that describes the causal dependencies among random variables. A common workflow involves first utilizing conditional independence properties on observation...
Online advertising platforms host hundreds of thousands of A/B tests, but the platform's delivery algorithm routes each creative to the audience it predicts will engage. Every two-arm test therefore c...
Triboelectric nanogenerators (TENGs), which operate independently of sunlight or fuel, can effectively harvest deep-sea mechanical energy (such as ocean currents and fluctuations) to power long-term l...
As the Gulf of Maine warms, characterizing seasonal baseline levels of the human pathogen Vibrio parahaemolyticus (Vp) in Eastern oysters (Crassostrea virginica) is crucial, along with synoptic enviro...
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