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ForkSCOPE: Charting the Agentic Garden of Forking Paths
Even with a fixed dataset and research question, data analysis involves many defensible decisions. Understanding how these choices …
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Probing the Stochastic Machine: Engaging with LLMs in Statistics Curricula Through Veridical Data Science
Large language models (LLMs) are interactive stochastic systems whose most consequential behaviors are still only partially understood. …
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Grading the Grader: Lessons from Evaluating an Agentic Data Analysis System
Agentic data analysis systems produce rich outputs, including code, numerical results, and verbal diagnostics. This makes them more …
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Target-Aware Linear Regression Under Distribution Shift
Distribution shift between training and deployment is a pervasive challenge for modern AI systems. In many cases, the target marginals …
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Calibrating Geophysical Predictions under Constrained Probabilistic Distributions
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Power Ensemble Aggregation for Improved Extreme Event AI Prediction
This paper addresses the critical challenge of improving predictions of climate extreme events, specifically heat waves, using machine …
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AI Education in Higher Education: A Taxonomy for Curriculum Reform and the Mission of Knowledge
Artificial intelligence (AI) is reshaping higher education, yet current debates often feel tangled, mixing concerns about pedagogy, …
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AI Education in Higher Education: A Taxonomy for Curriculum Reform and the Mission of Knowledge
Graph-Enabled Efficient Federated Bayesian Modeling
Federated Bayesian modeling requires combining evidence across distributed data holders while preserving posterior uncertainty and …
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Phase-Aligned Spectral Filtering for Decomposing Spatiotemporal Dynamics
Spatiotemporal dynamics is central to a wide range of applications from climatology, computer vision to neural sciences. From temporal …
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