Biblio
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Author Title Type [ Year
Filters: Author is Felix J. Herrmann and Keyword is Bayesian inference [Clear All Filters]
“InvertibleNetworks.jl: A Julia package for scalable normalizing flows”, Journal of Open Source Software, vol. 9, 2024.
, “Machine-learning enabled velocity-model building with uncertainty quantification”, ML4SEISMIC Partners Meeting. 2024.
, “Neural wave-based imaging with amortized uncertainty quantification”, ICL Seminar. 2024.
, “Neural wave-based imaging with amortized uncertainty quantification”, in Inverse Problems: Modelling and Simulation, 2024.
, “Normalizing Flows for Bayesian Experimental Design in Imaging Applications”, in EAGE Annual Conference Proceedings, 2024.
, “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.
, , “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, 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.
, “Inference of CO2 flow patterns – a feasibility study”, in Neural Information Processing Systems (NeurIPS), 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.
, “Refining Amortized Posterior Approximations using Gradient-Based Summary Statistics”, in 5th Symposium on Advances in Approximate Bayesian Inference, 2023.
, “Adjoint operators as summary functions in amortized Bayesian inference frameworks”, 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.
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