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Paper Citation Record · LEDGER

Deep Learning Surrogates for Real-Time Gas Emission Inversion

As of 21 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2506.14597.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.14597 v1

Coverage vector

measured 34 of 34 reference resolution

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measured 0 of 0 inbound itemization

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Reference resolution

34 of 34 outbound references displayed

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External citation measurements

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Outbound references

Observation 50ccd85f-7dba-4a6f-a97a-9ef3b6262890 · outbound

This paper cites State space modeling of multiple time series.Econometric Reviews, 10(1):1–59, 1991.

Deep Learning Surrogates for Real-Time Gas Emission Inversion State space modeling of multiple time series.Econometric Reviews, 10(1):1–59, 1991

Reference 1

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Observation 0b44b073-c52d-4c65-b47d-addd73c80842 · outbound

This paper cites A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking.IEEE Transactions on Signal Processing, 50(2):174–188, 2002.

Deep Learning Surrogates for Real-Time Gas Emission Inversion A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking.IEEE Transactions on Signal Processing, 50(2):174–188, 2002

Reference 2

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This paper cites The interacting multiple model algorithm for systems with Markovian switching coefficients.IEEE Transactions on Automatic Control, 33(8):780– 783, 2002.

Deep Learning Surrogates for Real-Time Gas Emission Inversion The interacting multiple model algorithm for systems with Markovian switching coefficients.IEEE Transactions on Automatic Control, 33(8):780– 783, 2002

Reference 3

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Observation bc713340-d463-47b8-9b0c-8b4f53d8e1c0 · outbound

This paper cites CRC press, 2011.

Deep Learning Surrogates for Real-Time Gas Emission Inversion CRC press, 2011

Reference 4

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Observation 6140f541-0766-4f00-873d-728388316564 · outbound

This paper cites Stochastic problems in physics and astronomy.Reviews of Modern Physics, 15(1):1, 1943.

Deep Learning Surrogates for Real-Time Gas Emission Inversion Stochastic problems in physics and astronomy.Reviews of Modern Physics, 15(1):1, 1943

Reference 5

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Observation d43981e2-ef93-4f48-bbc4-cea8217a27c1 · outbound

This paper cites Comparison of resampling schemes for particle filtering.

Deep Learning Surrogates for Real-Time Gas Emission Inversion Comparison of resampling schemes for particle filtering

Reference 6

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Observation 62f3eba5-aa95-4d31-98f6-0a71270a931c · outbound

This paper cites Scalable Monte Carlo for Bayesian Learning.

Deep Learning Surrogates for Real-Time Gas Emission Inversion Scalable Monte Carlo for Bayesian Learning

Reference 7

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Observation f2dc7304-4790-43db-adc3-91c8a1f2c708 · outbound

This paper cites Understanding the difficulty of training deep feedforward neural networks.

Deep Learning Surrogates for Real-Time Gas Emission Inversion Understanding the difficulty of training deep feedforward neural networks

Reference 8

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Observation 2850cf38-c6de-41a8-81db-30a33e844190 · outbound

This paper cites Novel approach to nonlinear/non- Gaussian Bayesian state estimation.

Deep Learning Surrogates for Real-Time Gas Emission Inversion Novel approach to nonlinear/non- Gaussian Bayesian state estimation

Reference 9

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Observation 214a3639-ecb6-4edf-bebc-2be9cd1cf1ab · outbound

This paper cites State-space models.Handbook of Econometrics, 4:3039–3080, 1994.

Deep Learning Surrogates for Real-Time Gas Emission Inversion State-space models.Handbook of Econometrics, 4:3039–3080, 1994

Reference 10

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Observation 8faad877-7828-4027-87fb-47641b8c4bb7 · outbound

This paper cites Methane emissions: remote mapping and source quantification using an open-path laser dispersion spectrometer.Geophysical Research Letters, 47(10), 2020.

Deep Learning Surrogates for Real-Time Gas Emission Inversion Methane emissions: remote mapping and source quantification using an open-path laser dispersion spectrometer.Geophysical Research Letters, 47(10), 2020

Reference 11

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Observation 730a7088-de8d-4f19-b618-861962ebd210 · outbound

This paper cites Mapping CO2 and CH4 emissions: field-trial evaluation of LightSource for remotely estimating the locations and mass emission rates of sources.

Deep Learning Surrogates for Real-Time Gas Emission Inversion Mapping CO2 and CH4 emissions: field-trial evaluation of LightSource for remotely estimating the locations and mass emission rates of sources

Reference 12

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Observation f65cc790-2cec-4feb-a1e7-67dfa73ee782 · outbound

This paper cites ΦFlow (PhiFlow): differentiable simulations for PyTorch, TensorFlow and Jax.

Deep Learning Surrogates for Real-Time Gas Emission Inversion ΦFlow (PhiFlow): differentiable simulations for PyTorch, TensorFlow and Jax

Reference 13

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Observation 3be04f09-4de6-497b-9f9d-fb51bffaa9dc · outbound

This paper cites Parameterizing state–space models for infectious disease dynamics by generalized profiling: measles in ontario.

Deep Learning Surrogates for Real-Time Gas Emission Inversion Parameterizing state–space models for infectious disease dynamics by generalized profiling: measles in ontario

Reference 14

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Observation e6178ab6-a196-4fc1-9304-0c1abe3df275 · outbound

This paper cites Academic Press, 1970.

Deep Learning Surrogates for Real-Time Gas Emission Inversion Academic Press, 1970

Reference 15

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Observation b6f60df8-2552-4c79-8445-b73ad6f7b472 · outbound

This paper cites A new approach to linear filtering and prediction problems.Journal of Basic Engineering, 1960.

Deep Learning Surrogates for Real-Time Gas Emission Inversion A new approach to linear filtering and prediction problems.Journal of Basic Engineering, 1960

Reference 16

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Observation ca141ceb-7f50-4c6e-9e41-b7d5ff3a6792 · outbound

This paper cites Monte Carlo filter and smoother for non-Gaussian nonlinear state space models.Journal of Computational and Graphical Statistics, 5(1):1–25, 1996.

Deep Learning Surrogates for Real-Time Gas Emission Inversion Monte Carlo filter and smoother for non-Gaussian nonlinear state space models.Journal of Computational and Graphical Statistics, 5(1):1–25, 1996

Reference 17

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Observation e23caf7a-7cd9-4257-82ea-805f9ec9205f · outbound

This paper cites Self-normalizing neural networks.Advances in Neural Information Processing Systems, 30, 2017.

Deep Learning Surrogates for Real-Time Gas Emission Inversion Self-normalizing neural networks.Advances in Neural Information Processing Systems, 30, 2017

Reference 18

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Observation 25e380cb-b0a9-42a1-8b87-c596045438c7 · outbound

This paper cites Sur les lois des mouvement des fluides, en ayant égard à l’adhesion des molecules.

Deep Learning Surrogates for Real-Time Gas Emission Inversion Sur les lois des mouvement des fluides, en ayant égard à l’adhesion des molecules

Reference 19

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Observation 3165543a-4206-4896-b0d6-12cede550e18 · outbound

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Deep Learning Surrogates for Real-Time Gas Emission Inversion Sur les lois du mouvement des fluides

Reference 20

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Observation c95fce9c-bebe-4b55-b33c-ddea15b2cac3 · outbound

This paper cites Particle learning methods for state and parameter estimation.

Deep Learning Surrogates for Real-Time Gas Emission Inversion Particle learning methods for state and parameter estimation

Reference 21

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Observation 85dff4af-6f6c-4bca-892c-a9639fd8e39f · outbound

This paper cites Probabilistic Inversion Modeling of Gas Emissions: A Gradient-Based MCMC Estimation of Gaussian Plume Parameters.

Deep Learning Surrogates for Real-Time Gas Emission Inversion Probabilistic Inversion Modeling of Gas Emissions: A Gradient-Based MCMC Estimation of Gaussian Plume Parameters

Reference 22

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Observation bd1e6496-fc56-4031-981b-bc1b5f8ccb9c · outbound

This paper cites The Oil & Gas Methane Partnership 2.0.

Deep Learning Surrogates for Real-Time Gas Emission Inversion The Oil & Gas Methane Partnership 2.0

Reference 23

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Observation ad163e70-133b-440b-8ff3-eea152173345 · outbound

This paper cites an unresolved cited work.

Deep Learning Surrogates for Real-Time Gas Emission Inversion Unresolved cited work

Reference 24

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Observation 94279496-463e-47b6-92cf-58cb744a0f40 · outbound

This paper cites Springer, 1999.

Deep Learning Surrogates for Real-Time Gas Emission Inversion Springer, 1999

Reference 25

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Observation 06844310-1cbe-4e5c-8273-6652dbc984f1 · outbound

This paper cites The perceptron: a probabilistic model for information storage and organiza- tion in the brain.Psychological Review, 65(6):386, 1958.

Deep Learning Surrogates for Real-Time Gas Emission Inversion The perceptron: a probabilistic model for information storage and organiza- tion in the brain.Psychological Review, 65(6):386, 1958

Reference 26

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Observation 3773b3b0-786d-4561-bcf5-3e7f0879b89d · outbound

This paper cites Global methane budget 2000–2020.Earth System Science Data, 17(5):1873–1958, 2025.

Deep Learning Surrogates for Real-Time Gas Emission Inversion Global methane budget 2000–2020.Earth System Science Data, 17(5):1873–1958, 2025

Reference 27

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Observation b5089da7-0dcc-4f75-b05e-e2779efb0493 · outbound

This paper cites Über Brownsche Molekularbewegung unter Einwirkung äußerer Kräfte und deren Zusammenhang mit der verallgemeinerten Diffusionsgleichung.Annalen der Physik, 353(24):1103–1112, 1916.

Deep Learning Surrogates for Real-Time Gas Emission Inversion Über Brownsche Molekularbewegung unter Einwirkung äußerer Kräfte und deren Zusammenhang mit der verallgemeinerten Diffusionsgleichung.Annalen der Physik, 353(24):1103–1112, 1916

Reference 28

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Observation 9b078d0f-2746-4401-9261-eaeca987a67c · outbound

This paper cites Cambridge University Press, 2014.

Deep Learning Surrogates for Real-Time Gas Emission Inversion Cambridge University Press, 2014

Reference 29

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Observation d12a09b3-9a7f-4ab8-aacb-7754177a8cc6 · outbound

This paper cites The mathematics of atmospheric dispersion modeling.Siam Review, 53(2):349– 372, 2011.

Deep Learning Surrogates for Real-Time Gas Emission Inversion The mathematics of atmospheric dispersion modeling.Siam Review, 53(2):349– 372, 2011

Reference 30

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Observation 21a1c953-bc6f-47b3-abb1-f9ea6fc0a5e0 · outbound

This paper cites Artech House, 2013.

Deep Learning Surrogates for Real-Time Gas Emission Inversion Artech House, 2013

Reference 31

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Observation 2439b718-2bff-4846-873b-b2377bfad5b4 · outbound

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Deep Learning Surrogates for Real-Time Gas Emission Inversion Unresolved cited work

Reference 32

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Observation ae097efc-1f51-43d8-bac2-dab338648911 · outbound

This paper cites A survey of transfer learning.Journal of Big Data, 3:1–40, 2016.

Deep Learning Surrogates for Real-Time Gas Emission Inversion A survey of transfer learning.Journal of Big Data, 3:1–40, 2016

Reference 33

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Observation 0a304b2d-00a1-41f0-9fd6-9c4755e808e6 · outbound

This paper cites Springer Science & Business Media, 2006.

Deep Learning Surrogates for Real-Time Gas Emission Inversion Springer Science & Business Media, 2006

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:55:48.349039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T19:55:48.273031Z digest=sha256:f67b3a0264b39b6de09a7494bebdf4bed1a9b8dbb64985cb6454b63391f57543

Pith citing papers

No inbound Pith citation observations are available.