Biblio
Export 120 results:
Author Title Type [ Year
] Filters: First Letter Of Last Name is O [Clear All Filters]
, “Low-cost uncertainty quantification for large-scale inverse problems”, ML4SEISMIC Partners Meeting. 2022.
, “Memory Efficient Invertible Neural Networks for 3D Photoacoustic Imaging”, TR-CSE-2022-2, 2022.
, “ML4Seismic open-source software: updates and developments”, ML4SEISMIC Partners Meeting. 2022.
, “Monitoring with sequential Bayesian inference”, 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.
, “Uncertainty-aware time-lapse CO$_2$ monitoring with learned end-to-end inversion”, ML4SEISMIC Partners Meeting. 2022.
, “Wave-equation based inversion with amortized variational Bayesian inference”, in EAGE Annual Conference Proceedings, 2022, p. Session 2: Velocity model building and imaging (different domains).
, “Adjoint operators enable fast and amortized machine learning based Bayesian uncertainty quantification”, in SPIE Medical Imaging Conference, 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.
, “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.
, “Inference of CO2 flow patterns – a feasibility study”, in Neural Information Processing Systems (NeurIPS), 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.
, “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.
, “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.
, “Towards generative seismic kriging with normalizing flows”, ML4SEISMIC Partners Meeting. 2023.
, “Uncertainty quantification so what? Leveraging probabilistic seismic inversion for experimental design”, ML4SEISMIC Partners Meeting. 2023.
, “Uncertainty-aware time-lapse monitoring of geological carbon storage with learned surrogates”, in Engineering Mechanics Institute Conference, 2023.