Biblio
] , “Abstractions and algorithms for efficient seismic inversion on accelerators”, in IMAGE Workshop on What's Next for FWI and its Derived Products, 2022.
, “Adjoint operators enable fast and amortized machine learning based Bayesian uncertainty quantification”, in SPIE Medical Imaging Conference, 2023.
, “A deep-learning based Bayesian approach to seismic imaging and uncertainty quantification”, in EAGE Annual Conference Proceedings, 2020.
, “Enabling uncertainty quantification for seismic data pre-processing using normalizing flows (NF)—an interpolation example”, in SEG Technical Program Expanded Abstracts, 2021, pp. 1515-1519.
, “Enhancing CO2 Leakage Detectability via Dataset Augmentation”, in International Meeting for Applied Geoscience and Energy, 2023.
, “InvertibleNetworks.jl - Memory efficient deep learning in Julia”, in JuliaCon, 2021.
, “Learned coupled inversion for carbon sequestration monitoring and forecasting with Fourier neural operators”, in International Meeting for Applied Geoscience and Energy Expanded Abstracts, 2022.
, “Learned imaging with constraints and uncertainty quantification”, in Neural Information Processing Systems (NeurIPS), 2019.
, “Learned non-linear simultenous source and corresponding supershot for seismic imaging.”, in International Meeting for Applied Geoscience and Energy, 2023.
, “Learning by example: fast reliability-aware seismic imaging with normalizing flows”, in SEG Technical Program Expanded Abstracts, 2021, pp. 1580-1585.
, “ML@scale using randomized linear algebra”, in Microsoft, 2021.
, “Monitoring Subsurface CO2 Plumes with Sequential Bayesian Inference”, in International Meeting for Applied Geoscience and Energy, 2023.
, “The Next Step: Interoperable Domain-Specific Programming”, in SIAM Conference on Computational Science and Engineering, 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.
, “Ultra-Low-Bitrate Speech Coding with Pretrained Transformers”, in Proceedings of INTERSPEECH, 2022.
, “An Uncertainty-Aware Digital Twin for Geological Carbon Storage”, in SIAM Conference on Uncertainty Quantification, 2024.
, “Uncertainty-aware time-lapse monitoring of geological carbon storage with learned surrogates”, in Engineering Mechanics Institute Conference, 2023.
, “Unsupervised data-guided uncertainty analysis in imaging and horizon tracking”, in SIAM Texas-Louisiana, 2020.
, “Digital twins in the era of generative AI”, The Leading Edge, vol. 42, 2023.
, “The importance of transfer learning in seismic modeling and imaging”, Geophysics, 2019.
, “Learned multiphysics inversion with differentiable programming and machine learning”, The Leading Edge, vol. 42, pp. 452-516, 2023.
, “Model-Parallel Fourier Neural Operators as Learned Surrogates for Large-Scale Parametric PDEs”, Computers & Geosciences, vol. 178, p. 105402, 2023.
, “Solving multiphysics-based inverse problems with learned surrogates and constraints”, Advanced Modeling and Simulation in Engineering Sciences, vol. 10, 2023.
, “WISE: full-Waveform variational Inference via Subsurface Extensions”, Geophysics, 2024.
, “Adjoint operators as summary functions in amortized Bayesian inference frameworks”, ML4SEISMIC Partners Meeting. 2022.