@conference {herrmann2026EAGEWSlmi,
	title = {Learned Multiphysics Inversion with Differentiable Programming \& Machine Learning: An open-source path from wave physics to CO$_{2}$ digital twins},
	booktitle = {EAGE Workshop: Open for Energy: Open Source, Open Data, Open Models, EAGE, Aberdeen},
	year = {2026},
	month = {6},
	keywords = {Bayesian inference, deep learning, EAGE, foundation models, full waveform inference, generative model, Imaging, Inverse problems, multiphysics, RTM, score, Summary Statistics, UK-NDR, Uncertainty quantification},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2026/herrmann2026EAGEWSlmi/slides.html},
	author = {Mathias Louboutin and Ipsita Bhar and Huseyin Tuna Erdinc and Felix J. Herrmann}
}
@conference {louboutin2022EAGEewi,
	title = {Enabling wave-based inversion on GPUs with randomized trace estimation},
	booktitle = {EAGE Annual Conference Proceedings},
	year = {2022},
	note = {(EAGE, Madrid)},
	month = {06},
	pages = {Seismic Wave Modelling and Least Square Migration 2 session},
	abstract = {By building on recent advances in the use of randomized trace estimation to drastically reduce the memory footprint of adjoint-state methods, we present and validate an imaging approach that can be executed exclusively on accelerators. Results obtained on field-realistic synthetic datasets, which include salt and anisotropy, show that our method produces high-fidelity images. These findings open the enticing perspective of 3D wave-based inversion technology with a memory footprint that matches the hardware and that runs exclusively on clusters of GPUs without the undesirable need to offload certain tasks to CPUs.},
	keywords = {EAGE, Image Volumes, inversion, RTM, SEAM, stochastic, TTI},
	doi = {10.3997/2214-4609.202210531},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2022/louboutin2022eageewi/louboutinp.html},
	presentation = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2022/louboutin2022eageewi/Jun-9-3-15-mloubout.pdf},
	software = {https://github.com/slimgroup/TimeProbeSeismic.jl},
	author = {Mathias Louboutin and Felix J. Herrmann}
}
@conference {rizzuti2020EAGEtwri,
	title = {Time-domain wavefield reconstruction inversion for large-scale seismics},
	booktitle = {EAGE Annual Conference Proceedings},
	year = {2020},
	note = {Accepted in EAGE, withdrawn due to logistical challenge},
	month = {1},
	abstract = {Wavefield reconstruction inversion is an imaging technique akin to full-waveform inversion, albeit based on a relaxed version of the wave equation. This relaxation aims to beat the multimodality typical of full-waveform inversion. However it prevents the use of time-marching solvers for the augmented equation and, as a consequence, cannot be straightforwardly employed to large 3D problems. In this work, we formulate a dual version of wavefield reconstruction inversion amenable to explicit time-domain solvers, yielding a robust and scalable inversion technique.},
	keywords = {3D, EAGE, Full-waveform inversion, Time-domain},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2020/rizzuti2020EAGEtwri/rizzuti2020EAGEtwri.html},
	author = {Gabrio Rizzuti and Mathias Louboutin and Rongrong Wang and Felix J. Herrmann}
}
@conference {herrmann2019EAGEHPCaii,
	title = {Accelerating ideation and innovation cheaply in the Cloud the power of abstraction, collaboration and reproducibility},
	booktitle = {4th EAGE Workshop on High-performance Computing},
	year = {2019},
	note = {(EAGE HPC Workshop, Dubai)},
	month = {10},
	keywords = {cloud, devito, EAGE, HPC, JUDI},
	presentation = {https://slim.gatech.edu/Publications/Public/Conferences/EAGEHPC/2019/herrmann2019EAGEHPCaii/herrmann2019EAGEHPCaii_pres.pdf},
	author = {Felix J. Herrmann and Charles Jones and Gerard Gorman and Jan H{\"u}ckelheim and Keegan Lensink and Paul H. J. Kelly and Navjot Kukreja and Henryk Modzelewski and Michael Lange and Mathias Louboutin and Fabio Luporini and James Selvages and Philipp A. Witte}
}
@conference {louboutin2017EAGEdns,
	title = {Data normalization strategies for full-waveform inversion},
	booktitle = {EAGE Annual Conference Proceedings},
	year = {2017},
	note = {(EAGE, Paris)},
	month = {06},
	abstract = {Amplitude mismatch is an inherent problem in seismic inversion. Most of the source estimation techniques are associated with amplitude uncertainty due to incomplete representation of the physics or estimation method parameters. Rewriting the inversion problem in an amplitude free formulation allows to mitigate the amplitude ambiguity and help the inversion process to converge. We present in this work two different strategies to lessen amplitude effects in seismic inversion, derive the corresponding update directions and show how we handle scaling error correctly in both the objective function and the gradient.},
	keywords = {EAGE, FWI, inversion, nonlinear, normalization},
	doi = {10.3997/2214-4609.201700720},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2017/louboutin2017EAGEdns/louboutin2017EAGEdns.html},
	presentation = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2017/louboutin2017EAGEdns/louboutin2017EAGEdns_poster.pdf},
	author = {Mathias Louboutin and Llu{\'\i}s Guasch and Felix J. Herrmann}
}
@conference {louboutin2017EAGEess,
	title = {Extending the search space of time-domain adjoint-state FWI with randomized implicit time shifts},
	booktitle = {EAGE Annual Conference Proceedings},
	year = {2017},
	note = {(EAGE, Paris)},
	month = {06},
	abstract = {Adjoint-state full-waveform inversion aims to obtain subsurface properties such as velocity, density or anisotropy parameters, from surface recorded data. As with any (non-stochastic) gradient based optimization procedure, the solution of this inversion procedure is to a large extend determined by the quality of the starting model. If this starting model is too far from the true model, these derivative-based optimizations will likely end up in local minima and erroneous inversion results. In certain cases, extension of the search space, e.g. by making the wavefields or focused matched sources additional unknowns, has removed some of these non-uniqueness issues but these rely on time-harmonic formulations. Here, we follow a different approach by combining an implicit extension of the velocity model, time compression techniques and recent results on stochastic sampling in non-smooth/non-convex optimization},
	keywords = {cycle skipping, EAGE, FWI, inversion, nonconvex, time domain},
	doi = {10.3997/2214-4609.201700831},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2017/louboutin2017EAGEess/louboutin2017EAGEess.html},
	presentation = {https://slim.gatech.edu/Publications/Public/Conferences/EAGE/2017/louboutin2017EAGEess/louboutin2017EAGEess_pres.pdf},
	author = {Mathias Louboutin and Felix J. Herrmann}
}
