Modern business intelligence demands speed, and utilizing AI tools for Excel is the ultimate way to hyper-charge your data workflows this year.
These short anomaly-detection puzzles are designed to illustrate how reasoning often depends on identifying inconsistencies ...
People are increasing "chatfishing," using AI apps to generate texts to their romantic interests. Sometimes they'll slip up ...
Abstract: Model predictive controllers use dynamics models to solve constrained optimal control problems. However, computational requirements for real-time control have limited their use to systems ...
Strategic initiative to accelerate practical quantum computing through cross-platform execution to reach fault-tolerant performance ...
It feels like there’s no escaping AI right now, whether you’re trying to type a sentence without being interrupted by a digital “assistant” or struggling to find a new refrigerator that doesn’t ...
Abstract: This communication proposes two novel error estimators suitable for the adaptive h-refinement of curvilinear nonconformal meshes in electromagnetic ...
Materials, slides, hands-on code and assignments for for the course "Introduction to computational social science" for the 2025 edition Here I will copy announcements posted on Stud.IP so that ...
Simplifying quantum simulations—symmetry can cut computational effort by several orders of magnitude
Quantum computer research is advancing at a rapid pace. Today's devices, however, still have significant limitations: For example, the length of a quantum computation is severely limited—that is, the ...
What defines a space first when entering: the sound or the visual impression? Architecture is often communicated through structure and surfaces, yet one of its most essential components moves unseen ...
One of the most fundamental processes in all of biology is the spontaneous organization of cells into clusters that divide and eventually turn into shapes – be they organs, wings, or limbs. Scientists ...
This work reviews CM-cfDNA methods applied to clinical oncology, emphasizing both machine learning (ML) techniques and mechanistic approaches. The latter integrate biological principles, enabling a ...
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