Biblio
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Author Title Type [ Year
Filters: Author is Felix J. Herrmann and Keyword is Inverse problems [Clear All Filters]
“Optimizing CO2 Storage Monitoring with Enhanced Rock Physics Modeling”, ML4SEISMIC Partners Meeting. 2024.
, “Physical Bayesian Inference for Two-Phase Flow Problems”, ML4SEISMIC Partners Meeting. 2024.
, “Probabilistic Joint Recovery Method for CO2 plume monitoring”, ML4SEISMIC Partners Meeting. 2024.
, “Reconstructing Permeability and Saturation in Reservoir Simulation Using Diffusion PDE Models”, ML4SEISMIC Partners Meeting. 2024.
, “SAGE – Subsurface foundational model with AI-driven Geostatical Extraction”, ML4SEISMIC Partners Meeting. 2024.
, , “Seismic monitoring of CO2 plume dynamics using ensemble Kalman filtering”, ML4SEISMIC Partners Meeting. 2024.
, “Sensitivity of Horizontal shear waves on Geological Carbon Storage”, ML4SEISMIC Partners Meeting. 2024.
, “Tucker Compression for Scalable Operator Learning in Large-Scale Parametric PDE Models”, ML4SEISMIC Partners Meeting. 2024.
, , “WISE: full-Waveform variational Inference via Subsurface Extensions”, Geophysics, vol. 89, 2024.
, “WISER: full-Waveform variational Inference via Subsurface Extensions with Refinements”, in International Meeting for Applied Geoscience and Energy, 2024.
, “Adjoint operators enable fast and amortized machine learning based Bayesian uncertainty quantification”, in SPIE Medical Imaging Conference, 2023.
, “Reliable amortized variational inference with physics-based latent distribution correction”, Geophysics, vol. 88, 2023.
, “Solving multiphysics-based inverse problems with learned surrogates and constraints”, Advanced Modeling and Simulation in Engineering Sciences, vol. 10, 2023.
, “Solving PDE-based inverse problems with learned surrogates and constraints”, HotCSE Seminar. 2023.
, “Adjoint operators as summary functions in amortized Bayesian inference frameworks”, ML4SEISMIC Partners Meeting. 2022.
, “Low-cost uncertainty quantification for large-scale inverse problems”, ML4SEISMIC Partners Meeting. 2022.
, “Normalizing flows for regularization of 3D seismic inverse problems”, ML4SEISMIC Partners Meeting. 2022.
, “Reliable amortized variational inference with conditional normalizing flows via physics-based latent distribution correction”, in IMAGE Workshop on Subsurface Uncertainty Description and Estimation - Moving Away from Single Prediction with Distribution Learning, 2022.
, “Deep Bayesian Inference for Task-based Seismic Imaging”, in KAUST, 2021.
, “Preconditioned training of normalizing flows for variational inference in inverse problems”, in 3rd Symposium on Advances in Approximate Bayesian Inference, 2021.
, “Generalized Minkowski sets for the regularization of inverse problems”, in SIAM Conference on Mathematical and Computational Issues in the Geosciences, 2019.
, “Intersections and sums of sets for the regularization of inverse problems”, in Canadian Mathematical Society Winter Meeting, 2018.
, “Domain-specific abstractions for full-waveform inversion”, in SIAM Conference on Computational Science and Engineering, 2017.
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