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Supervised machine learning models are receiving increasing attention in electricity theft detection due to their high detection accuracy. However, their performance depends on a massive amount of labeled training data, which comes from time-consuming and ...
We conduct two survey experiments to study which information people choose to consume and how it affects their beliefs. In the first experiment, respondents choose between optimistic and pessimistic article headlines related to the COVID-19 pandemic and ar ...
2024
We introduce a class of quantum optical Hamiltonians characterized by three-body couplings and propose a circuit-QED scheme based on state-of-the-art technology that implements the considered model. Unlike two-body light-matter interactions, this three-bod ...
AMER PHYSICAL SOC2023
The technological advancements of the past decades have allowed transforming an increasing part of our daily actions and decisions into storable data, leading to a radical change in the scale and scope of available data in relation to virtually any object ...
Many methods exist to model snow densification in order to calculate the depth of a single snow layer or the depth of the total snow cover from its mass. Most of these densification models need to be tightly integrated with an accumulation and melt model a ...
Measuring bathymetry has always been a major scientific and technological challenge. In this work, we used a deep learning technique for inferring bathymetry from the depth-averaged velocity field. The training of the neural network is based on 5742 labora ...
The use of machine learning for predicting ecotoxicological outcomes is promising, but underutilized. The curation of data with informative features requires both expertise in machine learning as well as a strong biological and ecotoxicological background, ...
The electron self-interaction is a long-standing problem in density functional theory and is particularly critical in the description of polarons. Polarons are quasiparticles involving charge localization coupled with self-induced lattice distortions. Sinc ...
The Obukhov-Corrsin theory of scalar turbulence [21, 54] advances quantitative predictions on passive-scalar advection in a turbulent regime and can be regarded as the analogue for passive scalars of Kolmogorov's K41 theory of fully developed turbulence [4 ...
Benchmarking of scATAC-seq protocols demonstrates the effects of data quality on downstream analyses. Single-cell assay for transposase-accessible chromatin by sequencing (scATAC-seq) has emerged as a powerful tool for dissecting regulatory landscapes and ...
