Ultrasound-trained models top test of AI image similarity
A preprint finds ultrasound-trained models best matched classifier confidence in B-mode ultrasound, based on selected computational tests.
A preprint finds ultrasound-trained models best matched classifier confidence in B-mode ultrasound, based on selected computational tests.
A mathematical preprint proposes transition rules linking two optimization regimes, with faster early progress reported in selected numerical tests.
A JWST preprint models two brown dwarfs, finding contrasting silicate clouds, differing chemistry, and a possible thermal inversion in one atmosphere.
A theoretical preprint proposes exact and reduced models for superconducting circuits across resonator, metamaterial and waveguide settings.
A preprint reports that identifier-renaming attacks alter code-search rankings across models and languages, while defenses trade utility for robustness.
A preprint reports higher delivery, lower latency and stronger retention for adaptive wireless coding in simulations, plus a small hardware test.
A preprint models how beliefs about the best decision can strengthen robust optimization, while showing gains depend on assumptions and uncertainty.
An arXiv preprint reports Robust CurveMoE gains in clean, norm-specific and combined adversarial accuracy on CIFAR-100 and ImageNet-100.
A preprint compares neural networks and reduced-order models for reacting jet flows, finding task-dependent accuracy and predictions at new spacings.
A preprint finds branch-dependent links between neutrino CP violation, mass and strong CP, with sizable effects in selected model benchmarks.
A preprint presents a geometric, surgery-based extension of Reshetikhin–Turaev theory and classifies linear representations in 3D bordism settings.
An arXiv preprint explains how torsion-balance spectra can bound known torque signals and stochastic noise using Cavendish and Yan benchmarks.