LAUSR

Deep Learning Phase Pickers: How Well Can Existing Models Detect Hydraulic-Fracturing Induced Microseismicity from a Borehole Array?

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0 Published in 2024 at "Geophysical Journal International"

DOI: 10.1093/gji/ggae386

Abstract: Deep learning (DL) phase picking models have proven effective in processing large volumes of seismic data, including successfully detecting earthquakes missed by other standard detection methods. Despite their success, the applicability of existing extensively-trained DL… read more here.

Keywords: deep learning; learning phase; fracturing induced; models detect ... See more keywords

Machine Learning the Phase Diagram of a Strongly Interacting Fermi Gas.

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3 Published in 2023 at "Physical review letters"

DOI: 10.1103/physrevlett.130.203401

Abstract: We determine the phase diagram of strongly correlated fermions in the crossover from Bose-Einstein condensates of molecules (BEC) to Cooper pairs of fermions (BCS) utilizing an artificial neural network. By applying advanced image recognition techniques… read more here.

Keywords: learning phase; phase diagram; diagram strongly; machine learning ... See more keywords

NeuralPUMA: Learning to Phase Unwrap Through Differentiable Graph Cuts

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0 Published in 2024 at "IEEE Transactions on Signal Processing"

DOI: 10.1109/tsp.2023.3344356

Abstract: Deep learning solutions have recently demonstrated remarkable performance in phase unwrapping by approaching the problem as a semantic segmentation task. However, these solutions lack explainability and robustness to unseen conditions, and they often need a… read more here.

Keywords: graph cuts; deep learning; learning phase; neuralpuma learning ... See more keywords

Implementing non-invasive prenatal testing for aneuploidy in a national healthcare system: global challenges and national solutions

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0 Published in 2017 at "BMC Health Services Research"

DOI: 10.1186/s12913-017-2618-0

Abstract: BackgroundSince the introduction of non-invasive prenatal testing (NIPT) in 2011, mainly by commercial companies, a growing demand for NIPT from the public and healthcare professionals has been putting pressure on the healthcare systems of various… read more here.

Keywords: learning phase; invasive prenatal; prenatal testing; non invasive ... See more keywords

Machine Learning Phase Classification of Thermoelectric Materials

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0 Published in 2025 at "Materials"

DOI: 10.3390/ma18204726

Abstract: In this study, we employ a Support Vector Machine (SVM) model to efficiently classify the phases of thermoelectric (TE) alloys. While ab initio calculations and experiments have explored the phases of functional TE materials, the… read more here.

Keywords: classification; materials machine; learning phase; thermoelectric materials ... See more keywords