Biblio
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] Filters: Keyword is conditional normalizing flows [Clear All Filters]
, “GENERATIVE MODELS FOR UNCERTAINTY QUANTIFICATION OF MEDICAL AND SEISMIC IMAGING”, Georgia Institute of Technology, Atlanta, 2024.
, “InvertibleNetworks.jl: A Julia package for scalable normalizing flows”, Journal of Open Source Software, vol. 9, 2024.
, “Neural wave-based imaging with amortized uncertainty quantification”, in Inverse Problems: Modelling and Simulation, 2024.
, “Neural wave-based imaging with amortized uncertainty quantification”, ICL Seminar. 2024.
, “Optimizing CO2 Storage Monitoring with Enhanced Rock Physics Modeling”, ML4SEISMIC Partners Meeting. 2024.
, “Solving geophysical inverse problems with scientific machine learning”, Georgia Institute of Technology, Atlanta, 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.
, “Inference of CO2 flow patterns – a feasibility study”, in Neural Information Processing Systems (NeurIPS), 2023.
, “Refining Amortized Posterior Approximations using Gradient-Based Summary Statistics”, in 5th Symposium on Advances in Approximate Bayesian Inference, 2023.
, “Uncertainty-aware time-lapse monitoring of geological carbon storage with learned surrogates”, in Engineering Mechanics Institute Conference, 2023.
, “WISE: Full-waveform Inference with Subsurface Extensions”, ML4SEISMIC Partners Meeting. 2023.
, “Monitoring with sequential Bayesian inference”, ML4SEISMIC Partners Meeting. 2022.
, “Uncertainty-aware time-lapse CO$_2$ monitoring with learned end-to-end inversion”, ML4SEISMIC Partners Meeting. 2022.