Biblio
] , “Learned imaging with constraints and uncertainty quantification”, HotCSE Seminar. 2019.
, “Learned iterative solvers for the Helmholtz equation”, in EAGE Annual Conference Proceedings, 2019.
, “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.
, “Learned wave-based imaging - variational inference at scale”, in Delft, 2021.
, “Learning by example: fast reliability-aware seismic imaging with normalizing flows”, in SEG Technical Program Expanded Abstracts, 2021, pp. 1580-1585.
, “Low-cost uncertainty quantification for large-scale inverse problems”, ML4SEISMIC Partners Meeting. 2022.
, “Low-memory stochastic backpropagation with multi-channel randomized trace estimation”, TR-CSE-2021-1, 2021.
, “ML@scale using randomized linear algebra”, in Microsoft, 2021.
, “Multifidelity conditional normalizing flows for physics-guided Bayesian inference”, ML4SEISMIC Partners Meeting. 2021.
, “Neural network augmented wave-equation simulation”, Georgia Institute of Technology, TR-CSE-2019-1, 2019.
, “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.
, “Optimized time-lapse acquisition design via spectral gap ratio minimization”, Geophysics, vol. 88, pp. A19-A23, 2023.
, “Parameterizing uncertainty by deep invertible networks, an application to reservoir characterization”, in SEG Technical Program Expanded Abstracts, 2020, pp. 1541-1545.
, “Photoacoustic Imaging with Conditional Priors from Normalizing Flows”, in Neural Information Processing Systems (NeurIPS), 2021.
, “The power of abstraction in Computational Exploration Seismology”, in Smoky Mountains Computational Sciences and Engineering Conference, 2018.
, “Preconditioned training of normalizing flows for variational inference in inverse problems”, in 3rd Symposium on Advances in Approximate Bayesian Inference, 2021.
, “Refining Amortized Posterior Approximations using Gradient-Based Summary Statistics”, in 5th Symposium on Advances in Approximate Bayesian Inference, 2023.
, “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.
, “Reliable amortized variational inference with physics-based latent distribution correction”, Geophysics, vol. 88, 2023.
, “Seismic data interpolation with Generative Adversarial Networks”, SINBAD Fall consortium talks. SINBAD, 2017.
, “Seismic data reconstruction with Generative Adversarial Networks”, in EAGE Annual Conference Proceedings, 2018.
, “Seismic Imaging with Uncertainty Quantification: Sampling from the Posterior with Generative Networks”, in SIAM Conference on Imaging Science, 2020.
, “Seismic Velocity Inversion and Uncertainty Quantification Using Conditional Normalizing Flows”, in AGU Annual Meeting, 2021, p. U12A-03.