Biblio
] , “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).
, “Uncertainty quantification in imaging and automatic horizon tracking—a Bayesian deep-prior based approach”, ML4SEISMIC Partners Meeting. 2021.
, “Surface-related multiple elimination with deep learning”, in SEG Technical Program Expanded Abstracts, 2019, pp. 4629-4634.
, “Seismic data interpolation with Generative Adversarial Networks”, SINBAD Fall consortium talks. SINBAD, 2017.
, “Deep Bayesian inference for seismic imaging with tasks”, Geophysics, vol. 87, pp. 281-302, 2022.
, “The importance of transfer learning in seismic modeling and imaging”, Geophysics, 2019.
, “Weak deep priors for seismic imaging”, in SEG Technical Program Expanded Abstracts, 2020, pp. 2998-3002.
, “Deep Bayesian Inference for Task-based Seismic Imaging”, in KAUST, 2021.
, “Velocity continuation with Fourier neural operators for accelerated uncertainty quantification”, in International Meeting for Applied Geoscience and Energy Expanded Abstracts, 2022.
, “Fast and reliability-aware seismic imaging with conditional normalizing flows”, in Intelligent illumination of the Earth, 2021.
, “Deep generative models for solving geophysical inverse problems”, Georgia Institute of Technology, Atlanta, 2022.
, “Deep-learning based ocean bottom seismic wavefield recovery”, in SEG Technical Program Expanded Abstracts, 2019, pp. 2232-2237.
, “A deep-learning based Bayesian approach to seismic imaging and uncertainty quantification”, in EAGE Annual Conference Proceedings, 2020.
, “Preconditioned training of normalizing flows for variational inference in inverse problems”, in 3rd Symposium on Advances in Approximate Bayesian Inference, 2021.
, “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.
, “Unsupervised data-guided uncertainty analysis in imaging and horizon tracking”, in SIAM Texas-Louisiana, 2020.
, “Learning by example: fast reliability-aware seismic imaging with normalizing flows”, in SEG Technical Program Expanded Abstracts, 2021, pp. 1580-1585.
, “Seismic data reconstruction with Generative Adversarial Networks”, in EAGE Annual Conference Proceedings, 2018.
, “Reliable amortized variational inference with physics-based latent distribution correction”, Geophysics, vol. 88, 2023.
, “Low-cost uncertainty quantification for large-scale inverse problems”, ML4SEISMIC Partners Meeting. 2022.
, “Seismic Imaging with Uncertainty Quantification: Sampling from the Posterior with Generative Networks”, in SIAM Conference on Imaging Science, 2020.
, “Deep Convolutional Neural Networks in prestack seismic–-two exploratory examples”, in SEG Technical Program Expanded Abstracts, 2018, pp. 2196-2200.
, “Ultra-Low-Bitrate Speech Coding with Pretrained Transformers”, in Proceedings of INTERSPEECH, 2022.
, “A deep-learning based Bayesian approach to seismic imaging and uncertainty quantification”, GT SEG Student Chapter. 2020.
, “Neural network augmented wave-equation simulation”, Georgia Institute of Technology, TR-CSE-2019-1, 2019.