The divergence of ASIC designs makes it difficult to run commonly used modern sequencing analysis pipelines due to software ...

Nvidia invests in accelerating the transition from experimental to practical quantum computing via AI-driven quantum error ...

Planning around tariff disruption echoes the pandemic, a moment the industry did not always meet with agility or savvy ...

Current methodologies for solving UC problems predominantly rely on mixed-integer linear programming and are supplemented by ... To address these limitations, this article proposes a constrained graph ...

Specifically, for a general linear image formation model, we first formulate a convex quadratic programming ... called gradient graph Laplacian regularizer (GGLR) that promotes piecewise planar (PWP) ...

Multiple programming languages will be ... and regression (linear, nonlinear), unsupervised learning (MLE, MAP, clustering, PCA, dimensionality reduction), graphical models, reasoning under ...

In a recent advance, a multi-disciplinary team of researchers developed a machine learning framework that adapts to changes in the geometry of the physical settings of PDEs. Called DIMON, the new ...

Note that it will run both algorithms, and the greedy will most likely fail I was inspired by a youtube video from Polylog, discussing Sudoku and how it relates to graph theory. I did not realize it ...

I ran ColPack (DISTANCE_ONE) on some of the publicly available data sets for comparison. The results are in the following table. On all of the instances, our algorithm is as good or better than the ...

This book focuses on computational intelligence techniques and their applications — fast-growing and promising research topics that have drawn a great deal of attention from researchers over the years ...

NVIDIA continues to push the boundaries of open AI development by open-sourcing its Open Code Reasoning (OCR) model suite — a trio of high-performance large language models purpose-built for code ...