Perceived similarity offers a window into the mental representations underlying our ability to make sense of our visual world, yet, the collection of similarity judgments quickly becomes infeasible ...

MULGONET combines deep learning and multi-omics analysis to predict tumor recurrence, addressing interpretability and ...

When exploring their surroundings, communicating with others and expressing themselves, humans can perform a wide range of body motions. The ability to realistically replicate these motions, applying ...

Abstract: Hierarchical Kriging (HK) is a promising surrogate model to fuse multi-fidelity data ... To mitigate the curse of dimensionality of HK for high-dimensional problems, an infinite-width ...

One notable missing feature in most ANN models is top-down feedback, i.e. projections from higher-order layers to lower-order layers in the network. Top-down feedback is ubiquitous in the brain, and ...

it's a strategic move toward future-proofing an organization's network infrastructure, ensuring it can support the demands of tomorrow as well as today. WWT developed this maturity model to help ...

Objectives The Esther Network (EN) model, a person-centred care innovation in Sweden ... Embedded cultural influences such as the need for order and hierarchical structures were both barriers to, and ...

You can often find her with a novel and an iced coffee during her time off. An "open-weights" AI model is a kind of middle ground between open- and closed-source approaches. Weights are how AI ...

Seven months after the finalization of the merger of Jefferson Health and Lehigh Valley Health Network, little has ... However, for now, that model will be limited to the Lehigh regions.

Additionally, label generation methods based on model predictions often show poor adaptability across different datasets, necessitating customization of the classification network. Therefore, we ...