Sobol
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Related Articles from SNS
From data to decisions: Bayesian modelling and global sensitivity analysis for flotation control
arXiv:2606.06173v1 Announce Type: new Abstract: This work presents a data-driven framework for interpretable modelling and decision support in flotation systems, integrating Gaussian Process (GP) regression with Global Sensitivity Analysis (GSA) via Sobol indices and local interpretability using SHapley Additive exPlanations (SHAP). Based on laboratory-scale experimental data, a static GP surrogate model is developed to capture how superficial air velocity, overflowing froth velocity, froth...
Signal One review – Dennis Quaid and David Thewlis star in high-concept, low-risk first contact yarn
Sci-fi about the inventor of a device to communicate with aliens, in which scientists spend too much time talking astrophysics at each otherSteven Spielberg’s Disclosure Day is not alone in the universe. It is now joined by another sci-fi about Earth’s first contact with intelligent extraterrestrial life in the form of a high-concept, low-risk, talky drama from writer-director Jonathan Sobol. It stars Isabelle Fuhrman as Dr Annika Cask, a brilliant young computer scientist, already famous...
U-Net-Accelerated Quality-Diversity Optimization for Climate-Adaptive Urban Layouts
arXiv:2606.04658v1 Announce Type: new Abstract: Optimizing urban layouts for climate adaptation requires balancing building density with cold-air ventilation. Because physics-based climate simulations are computationally expensive, planners typically evaluate fewer than ten manual designs. \gls{qd} algorithms offer a way to systematically illuminate the design space, but they require surrogate models to be practical.
Epidemiology of Model Collapse: Modeling Synthetic Data Contamination via Bilayer SIR Dynamics
arXiv:2606.05168v1 Announce Type: new Abstract: Training on synthetic data causes model collapse, but existing analyses treat this as single-chain degradation. In reality, the AI ecosystem involves cross-contamination: models ingest synthetic data from other models, produce new synthetic text, and contaminate shared corpora. We propose a bilayer coupled SIR/SIRS framework -- a phenomenological mean-field model treating data corpora and AI models as two interacting populations, each with...