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Paper Citation Record · LEDGER

Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing

As of 13 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2607.28535.

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pith.paper-citation-record.v1
2607.28535 v1

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Outbound references

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This paper cites Geophysics 83, R63–R75.

Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Geophysics 83, R63–R75

Reference 11

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This paper cites SIAM Journal on Imaging Sciences 11, 376–406.

Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing SIAM Journal on Imaging Sciences 11, 376–406

Reference 12

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This paper cites Journal of Geophysical Research: Solid Earth 123, 2984–2999.

Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Journal of Geophysical Research: Solid Earth 123, 2984–2999

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This paper cites Geophysics 86, R711–R721.

Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Geophysics 86, R711–R721

Reference 17

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This paper cites What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?.

Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?

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This paper cites Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles.

Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles

Reference 20

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This paper cites Math- ematical Geosciences 52, 53–79.

Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Math- ematical Geosciences 52, 53–79

Reference 23

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This paper cites Geophysical Prospecting 61, 1114–1134.

Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Geophysical Prospecting 61, 1114–1134

Reference 24

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Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Geophysics 84, R989–R1001

Reference 25

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This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.

Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing PyTorch: An Imperative Style, High-Performance Deep Learning Library

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This paper cites Journal of Computational Physics 378, 686–707.

Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Journal of Computational Physics 378, 686–707

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Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Seismic Full-Waveform Inversion Using Deep Learning Tools and Techniques

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Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Geophysics 85, R87–R99

Reference 36

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Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Geophysics 74, WCC1–WCC26

Reference 38

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Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Ma- chine Learning 92, 349–376

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Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Computers & Geosciences 155, 104833

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Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Geo- physics 81, R429–R445

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Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing IEEE Transactions on Computational Imaging 6, 419–433

Reference 43

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Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Geophysics 89, A23–A28

Reference 44

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Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Computer Methods in Applied Mechanics and Engineering 416, 116300

Reference 45

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Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Geophysics 49, 1259–1266

Reference 1984

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Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Physica D: Nonlinear Phenomena 60, 259–268

Reference 1992

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Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Geophysics 60, 1457–1473

Reference 1995

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Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Proceedings of the National Academy of Sciences 93, 1591–1595

Reference 1996

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Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Geophysics 64, 888–901

Reference 1999

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Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Geophysics 69, 231–248

Reference 2004

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Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Springer, New York

Reference 2005

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Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing The Leading Edge 25, 156–166

Reference 2006

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Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Journal of Fourier Analysis and Applications 14, 877–905

Reference 2008

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Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Geophysics 74, WCC105–WCC118

Reference 2009

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Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Foundations and Trends in Machine Learning 3, 1–122

Reference 2011

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Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Geophysical Journal International 195, 661–667

Reference 2013

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Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning

Reference 2016

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Reference 2017

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Observation ccc9c71c-d511-4a73-b515-46626c0576b7 · outbound

This paper cites The Leading Edge 37, 58–66.

Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing The Leading Edge 37, 58–66

Reference 2018

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Observation 8d3edb29-ccee-44e9-b0d8-21ec75192efb · outbound

This paper cites Geophysical Journal International 218, 855–872.

Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Geophysical Journal International 218, 855–872

Reference 2019

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Observation 384f0bb0-803f-4c5b-9d81-01c35b98f96c · outbound

This paper cites Journal of Geophysical Research: Solid Earth 125, e2019JB018428.

Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Journal of Geophysical Research: Solid Earth 125, e2019JB018428

Reference 2020

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verified exact
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Observation 3e18e3e1-fcae-45e3-a866-041bc751ec05 · outbound

This paper cites IEEE Signal Processing Magazine 38, 89–119.

Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing IEEE Signal Processing Magazine 38, 89–119

Reference 2021

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Observation 56f7896a-e0d1-4594-ae4d-fc4f57f72212 · outbound

This paper cites OpenFWI: Large-Scale Multi-Structural Benchmark Datasets for Seismic Full Waveform Inversion.

Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing OpenFWI: Large-Scale Multi-Structural Benchmark Datasets for Seismic Full Waveform Inversion

Reference 2022

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Observation 66248df9-46a7-456f-bf9e-24f64c4e960a · outbound

This paper cites Foundations and Trends in Machine Learning 16, 494–591.

Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing Foundations and Trends in Machine Learning 16, 494–591

Reference 2023

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Reference 2024

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Observation b10f5b83-11c5-4a03-9389-1d11f0e999eb · outbound

This paper cites IEEE Transactions on Geoscience and Remote Sensing Under review; EarthArXiv preprint, doi:10.31223/X56J49.

Reliability-calibrated deep residual full-waveform inversion using geometry-invariant physics encoding: synthetic validation and zero-shot Marmousi-2 testing IEEE Transactions on Geoscience and Remote Sensing Under review; EarthArXiv preprint, doi:10.31223/X56J49

Reference 2026

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verified exact
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Pith citing papers

No inbound Pith citation observations are available.