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Physics of Eclipsing Binaries. V. General Framework for Solving the Inverse Problem

• Authors : Conroy, Kyle E.; Kochoska, Angela; Hey, Daniel

• Source: Conroy, K E, Kochoska, A, Hey, D, Pablo, H, Hambleton, K M, Jones, D, Giammarco, J, Abdul-Masih, M & Prša, A 2020, 'Physics of Eclipsing Binaries. V. General Framework for Solving the

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Physics of Eclipsing Binaries. V. General Framework for Solving the Inverse Problem

• Authors : Conroy, Kyle E.; Kochoska, Angela; Hey, Daniel

• Source: Conroy, K E, Kochoska, A, Hey, D, Pablo, H, Hambleton, K M, Jones, D, Giammarco, J, Abdul-Masih, M & Prša, A 2020, 'Physics of Eclipsing Binaries. V. General Framework for Solving the

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To mask or not to mask? Investigating the impact of accounting for spatial frequency distributions and susceptibility sources on QSM quality

• Authors : Sandgaard, Anders Dyhr; Shemesh, Noam; Jespersen, Sune Nørhøj

Subjects: fitting; inverse problem; Larmor frequency

• Source: Sandgaard, A D, Shemesh, N, Jespersen, S N & Kiselev, V G 2023, 'To mask or not to mask? Investigating the impact of accounting for spatial frequency distributions and susceptibility sources on QSM

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To mask or not to mask? Investigating the impact of accounting for spatial frequency distributions and susceptibility sources on QSM quality

• Authors : Sandgaard, Anders Dyhr; Shemesh, Noam; Jespersen, Sune Nørhøj

Subjects: fitting; inverse problem; Larmor frequency

• Source: Sandgaard, A D, Shemesh, N, Jespersen, S N & Kiselev, V G 2023, 'To mask or not to mask? Investigating the impact of accounting for spatial frequency distributions and susceptibility sources on QSM

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Estimating T 2 from surface NMR FID data using a forward model based on the full-Bloch equation

• Authors : Grombacher, Denys; Fiandaca, Gianluca; Auken, Esben

Subjects: Electromagnetic methods; Hydrogeophysics; Inverse problem

• Source: Grombacher, D, Fiandaca, G & Auken, E 2019, 'Estimating T 2 from surface NMR FID data using a forward model based on the full-Bloch equation', Geophysical Journal International, vol. 218, no. 3, pp.

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Estimating T 2 from surface NMR FID data using a forward model based on the full-Bloch equation

• Authors : Grombacher, Denys; Fiandaca, Gianluca; Auken, Esben

Subjects: Electromagnetic methods; Hydrogeophysics; Inverse problem

• Source: Grombacher, D, Fiandaca, G & Auken, E 2019, 'Estimating T 2 from surface NMR FID data using a forward model based on the full-Bloch equation', Geophysical Journal International, vol. 218, no. 3, pp.

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Stochastic inversion of time-lapse electrical resistivity tomography data by means of an adaptive ensemble-based approach

• Authors : Vinciguerra, Alessandro; Aleardi, Mattia; Madsen, Line Meldgaard

Subjects: inversion; resistivity; time lapse

• Source: Vinciguerra, A, Aleardi, M, Madsen, L M, Bording, T S, Christiansen, A V & Stucchi, E 2024, 'Stochastic inversion of time-lapse electrical resistivity tomography data by means of an adaptive

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Stochastic inversion of time-lapse electrical resistivity tomography data by means of an adaptive ensemble-based approach

• Authors : Vinciguerra, Alessandro; Aleardi, Mattia; Madsen, Line Meldgaard

Subjects: inversion; resistivity; time lapse

• Source: Vinciguerra, A, Aleardi, M, Madsen, L M, Bording, T S, Christiansen, A V & Stucchi, E 2024, 'Stochastic inversion of time-lapse electrical resistivity tomography data by means of an adaptive

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Use of Machine Learning to Estimate Statistics of the Posterior Distribution in Probabilistic Inverse Problems—An Application to Airborne EM Data

• Authors : Hansen, T. M.; Finlay, C. C.

Subjects: inversion; machine learning; neural network

• Source: Hansen, T M & Finlay, C C 2022, 'Use of Machine Learning to Estimate Statistics of the Posterior Distribution in Probabilistic Inverse Problems—An Application to

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Use of Machine Learning to Estimate Statistics of the Posterior Distribution in Probabilistic Inverse Problems—An Application to Airborne EM Data

• Authors : Hansen, T. M.; Finlay, C. C.

Subjects: inversion; machine learning; neural network

• Source: Hansen, T M & Finlay, C C 2022, 'Use of Machine Learning to Estimate Statistics of the Posterior Distribution in Probabilistic Inverse Problems—An Application to

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