Biblio
Export 136 results:
Author Title Type [ Year] Filters: Author is Mathias Louboutin [Clear All Filters]
“Digital Twins in the Era of Generative AI: Application to Geological CO 2 Storage”, HCMF Seminar. 2024.
, “Generative AI for full-waveform variational inference”, Georgia Tech Geophysics Seminar. 2024.
, “Normalizing Flows for Bayesian Experimental Design in Imaging Applications”, in SIAM Conference on Uncertainty Quantification, 2024.
, , “An Uncertainty-Aware Digital Twin for Geological Carbon Storage”, in SIAM Conference on Uncertainty Quantification, 2024.
, “WISE: full-Waveform variational Inference via Subsurface Extensions”, Geophysics, 2024.
, , “3D seismic survey design by maximizing the spectral gap”, in International Meeting for Applied Geoscience and Energy, 2023.
, “Amortized Bayesian Full Waveform Inversion and Experimental Design with Normalizing Flows”, in International Meeting for Applied Geoscience and Energy, 2023.
, “Amortized normalizing flows for transcranial ultrasound with uncertainty quantification”, in Medical Imaging with Deep Learning, 2023.
, “Coupled physics inversion for geological carbon storage monitoring”, in International Meeting for Applied Geoscience and Energy, 2023.
, “Derisking geological carbon storage from high-resolution time-lapse seismic to explainable leakage detection”, The Leading Edge, vol. 42, pp. 69-76, 2023.
, “Derisking geological storage with simulation-based seismic monitoring design and machine learning”, in Carbon, Capture, Utilization, and Storage, 2023.
, “End-to-end permeability inversion from prestack time-lapse seismic data: a case study on Compass model”, ML4SEISMIC Partners Meeting. 2023.
, “Enhancing CO2 Leakage Detectability via Dataset Augmentation”, in International Meeting for Applied Geoscience and Energy, 2023.
, “Fast neural FWI with amortized uncertainty quantification”, in International Meeting for Applied Geoscience and Energy, 2023.
, “Generative Seismic Kriging with Normalizing Flows”, in International Meeting for Applied Geoscience and Energy, 2023.
, “Improved automatic seismic CO2 leakage detection via dataset augmentation”, ML4SEISMIC Partners Meeting. 2023.
, , “Learned multiphysics inversion with differentiable programming and machine learning”, The Leading Edge, vol. 42, pp. 452-516, 2023.
, “Learned non-linear simultenous source and corresponding supershot for seismic imaging.”, in International Meeting for Applied Geoscience and Energy, 2023.
, “Model-Parallel Fourier Neural Operators as Learned Surrogates for Large-Scale Parametric PDEs”, Computers & Geosciences, vol. 178, p. 105402, 2023.
, “Monitoring subsurface CO2 plumes with learned sequential Bayesian inference”, ML4SEISMIC Partners Meeting. 2023.
, “Monitoring Subsurface CO2 Plumes with Sequential Bayesian Inference”, in International Meeting for Applied Geoscience and Energy, 2023.
, “The Next Step: Interoperable Domain-Specific Programming”, in SIAM Conference on Computational Science and Engineering, 2023.
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