Zobrazeno 1 - 10
of 35 596
pro vyhledávání: '"Brian, H"'
Active learning (AL) is a powerful sequential optimization approach that has shown great promise in the discovery of new materials. However, a major challenge remains the acquisition of the initial data and the development of workflows to generate ne
Externí odkaz:
http://arxiv.org/abs/2411.13689
In this work, we introduce a nonparametric clustering stopping rule algorithm based on the spatial median. Our proposed method aims to achieve the balance between the homogeneity within the clusters and the heterogeneity between clusters. The propose
Externí odkaz:
http://arxiv.org/abs/2410.18730
Autor:
Appleton, Robert J., Klinger, Daniel, Lee, Brian H., Taylor, Michael, Kim, Sohee, Blankenship, Samuel, Barnes, Brian C., Son, Steven F., Strachan, Alejandro
Data science and artificial intelligence are playing an increasingly important role in the physical sciences. Unfortunately, in the field of energetic materials data scarcity limits the accuracy and even applicability of ML tools. To address data lim
Externí odkaz:
http://arxiv.org/abs/2408.14488
Autor:
Levine, Joseph, Godfrey, Benjamin, Tyson, J. Anthony, Tripathi, S. Mani, Polin, Daniel, Aminaei, Amin, Kolner, Brian H., Stucky, Paul
We report new limits on the kinetic mixing strength of the dark photon spanning the mass range 0.21 -- 1.24 $\mu$eV corresponding to a frequency span of 50 -- 300 MHz. The Dark E-Field Radio experiment is a wide-band search for dark photon dark matte
Externí odkaz:
http://arxiv.org/abs/2405.20444
Condense phase molecular systems organize in wide range of distinct molecular configurations, including amorphous melt and glass as well as crystals often exhibiting polymorphism, that originate from their intricate intra- and intermolecular forces.
Externí odkaz:
http://arxiv.org/abs/2403.15266
Autor:
Lee, Brian H., Strachan, Alejandro
Data science and artificial intelligence have become an indispensable part of scientific research. While such methods rely on high-quality and large quantities of machine-readable scientific data, the current scientific data infrastructure faces sign
Externí odkaz:
http://arxiv.org/abs/2312.00902