Biblio
] , “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.
, “3D seismic survey design by maximizing the spectral gap”, in International Meeting for Applied Geoscience and Energy, 2023.
, “Adjoint operators enable fast and amortized machine learning based Bayesian uncertainty quantification”, in SPIE Medical Imaging Conference, 2023.
, “Amortized normalizing flows for transcranial ultrasound with uncertainty quantification”, in Medical Imaging with Deep Learning, 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.
, “Optimized time-lapse acquisition design via spectral gap ratio minimization”, Geophysics, vol. 88, pp. A19-A23, 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.
, “Uncertainty-aware time-lapse monitoring of geological carbon storage with learned surrogates”, in Engineering Mechanics Institute Conference, 2023.
, “Abstractions for at-scale seismic inversion”, in Rice Oil and Gas High Performance Computing Conference 2022, 2022, p. Thursday Workshop: Devito Training and Hackathon.
, “Accelerating innovation with software abstractions for scalable computational geophysics”, in International Meeting for Applied Geoscience and Energy Expanded Abstracts, 2022.
, “Adjoint operators as summary functions in amortized Bayesian inference frameworks”, ML4SEISMIC Partners Meeting. 2022.
, “Amortized velocity continuation with Fourier neural operators”, ML4SEISMIC Partners Meeting. 2022.
, “Capturing velocity-model uncertainty and two-phase flow with Fourier Neural Operators”, in EAGE Annual Conference Proceedings, 2022, p. AI in Geoscience and Geophysics: Current Trends and Future Prospects (Dedicated Session).
, “Deep Bayesian inference for seismic imaging with tasks”, Geophysics, vol. 87, pp. 281-302, 2022.
, “Deep generative models for solving geophysical inverse problems”, Georgia Institute of Technology, Atlanta, 2022.
, “Julia for Geoscience”, Transform. 2022.
, “Learned coupled inversion for carbon sequestration monitoring and forecasting with Fourier neural operators”, in International Meeting for Applied Geoscience and Energy Expanded Abstracts, 2022.
, “Low-cost uncertainty quantification for large-scale 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.
, “A simulation-free seismic survey design by maximizing the spectral gap”, in International Meeting for Applied Geoscience and Energy Expanded Abstracts, 2022.