Biblio
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Author Title Type [ Year
Filters: Keyword is invertible networks [Clear All Filters]
“Amortized normalizing flows for transcranial ultrasound with uncertainty quantification”, in Medical Imaging with Deep Learning, 2023.
, “Digital twins in the era of generative AI”, The Leading Edge, vol. 42, 2023.
, “Learned multiphysics inversion with differentiable programming and machine learning”, The Leading Edge, vol. 42, pp. 452-516, 2023.
, “Memory Efficient Invertible Neural Networks for 3D Photoacoustic Imaging”, TR-CSE-2022-2, 2022.
, “Faster Uncertainty Quantification for Inverse Problems with Conditional Normalizing Flows”, Georgia Institute of Technology, TR-CSE-2020-2, 2020.
, “Seismic Imaging with Uncertainty Quantification: Sampling from the Posterior with Generative Networks”, in SIAM Conference on Imaging Science, 2020.
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