Researchers from the University of Maryland, Lawrence Livermore, Columbia and TogetherAI have developed a training technique that triples LLM inference speed without auxiliary models or infrastructure ...
A multivariate analysis of electroencephalography activity reveals super-additive enhancements to the neural encoding of audiovisual stimuli, providing new insights into how the brain integrates ...
Abstract: In Deep Image Prior (DIP), a Convolutional Neural Network (CNN) is fitted to map a latent space to a degraded (e.g. noisy) image but in the process learns to reconstruct the clean image.
“Our goal was to build a clear mathematical bridge between abstract algebra and the experience of listening to music,” said study co-author Olga Ibragimova. “When we think of melodies as shapes we can ...
AI outputs vary because confidence varies. Corroboration and entity optimization turn inconsistent AI visibility into consistent presence.
Abstract: Coordinate classification is an efficient approach to 2-D human pose estimation (HPE), treating keypoint predictions as sub-pixel bins along horizontal and vertical axes, thereby avoiding ...
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For the past several years, America has been using its young people as lab rats in a sweeping, if not exactly thought-out, education experiment. Schools across the country have been lowering standards ...
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