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J. Obradors-Prats et al.
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Mathilde Adelinet et al.
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Raphael A. Viscarra Rossel et al.
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Matthew J. Cracknell et al.
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Tor Arne Johansen et al.
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M Bosch
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Confidence bounds of petrophysical predictions from conventional neural networks
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T Mukerji et al.
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Narrow-band spectral analysis and thin-bed tuning
KJ Marfurt et al.
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DP Hampson et al.
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