The Spallation Neutron Source (SNS) and the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory are two of the most advanced neutron scattering facilities in the world, where thousands of researchers each year probe the structure and dynamics of materials at the atomic scale, advancing quantum materials,...
Addi Malviya Thakur, John Hetrick, Peter F. Peterson et al.· Zenodo (CERN European Organi...· 0 citations
LUX-ZEPLIN (LZ) is the world’s most sensitive dark matter direct-detection experiment, acquiring over a petabyte of data per year. LZ also retains several terabytes of user-facing metadata describing detector conditions and data-processing environments needed for reproducible data selection and processing. These metada...
E. Mizrachi, LZ Collaboration· Zenodo (CERN European Organi...· 0 citations
AI is reshaping research software engineering on two fronts: AI components are increasingly embedded inside research software and science gateways that Research Software Engineers (RSEs) deliver, while AI-assisted and agentic coding tools are changing how RSEs build that software in the first place. This is especially...
I Luk Kim, Xiao Liu, Jungha Woo et al.· Zenodo (CERN European Organi...· 0 citations
Like many RSEs, my path to my current work was hardly linear and certainly not where I expected to be. I began my professional career in AmeriCorps, serving for two years at federally-qualified health centers, directly helping patients. I moved to research and trained as an epidemiologist. Now, I work as an embedded RS...
Malcolm Barrett· Zenodo (CERN European Organi...· 0 citations
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Background: Chronic obstructive pulmonary disease (COPD) requires sustained patient education, self-management, medication use, pulmonary rehabilitation, symptom monitoring, and guideline-concordant clinical management. Large language models (LLMs) may expand access to conversational health information, but their value...
Hanyu Du· Journal of Public Health and...· 0 citations
Workflows are a key technology for enabling complex scientific computations. They capture the interdependencies between processing steps in data analysis and simulation pipelines as well as the mechanisms to execute those steps reliably and efficiently. Workflows can capture complex processes, promote sharing and reuse...
Existing theory of momentum assumes that gradients arrive at every parameter at a roughly constant rate, an assumption violated in practice by heavy-tailed data distributions and modern architectures. We theoretically analyze the dynamics of two tractable models of momentum under sparse updates: a least squares model w...
We introduce a novel framework for uncertainty quantification of solution operators associated with stochastic partial differential equations (SPDEs). Although SPDEs play a central role in modeling complex physical systems under uncertainty, their practical use typically requires specifying the magnitude and structure...
Phuoc-Toan Huynh, Richard Archibald, Feng Bao· 0 citations
Comparing conditional distributions is a fundamental challenge in statistics and machine learning, with applications across a wide range of domains. While proposed methods for measuring discrepancies using kernel embeddings of distributions in a reproducing kernel Hilbert space (RKHS) provide powerful non-parametric te...
Peter Moskvichev, Siu Lun Chau, Dino Sejdinovic· 0 citations
We introduce structural causal bottleneck models (SCBMs), a novel class of structural causal models in which causal effects between high-dimensional variables are mediated by low-dimensional summary statistics, or *bottlenecks*. SCBMs provide a flexible framework for mechanism-specific, target-dependent dimension reduc...
Bayesian optimal experimental design is a principled framework for conducting experiments that leverages Bayesian inference to quantify how much information one can expect to gain from selecting a certain design. However, accurate Bayesian inference relies on the assumption that one's statistical model of the data-gene...
Yasir Zubayr Barlas, Sabina J. Sloman, Samuel Kaski· 0 citations
From neuroscience and genomics to systems biology and ecology, researchers rely on clustering similarity data to uncover modular structure. Most methods work in two steps: first reduce noise, then cluster. The first step runs without regard to the second: it forces arbitrary choices, discards useful information, and ca...
Magnus Neuman, Jelena Smiljani\'c, Martin Rosvall· 0 citations
Is your company’s AI sovereign? A practical guide for CIOs on AI vendor lock-in, EU Data Act switching, cloud sovereignty, and testing your exit plan before you need it. The post Sovereignty Is the Option to Leave appeared first on GPT-Lab.
