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Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “Normalizing flows for regularization of 3D seismic inverse problems”, ML4SEISMIC Partners Meeting. 2022.
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Richard Rex, Thomas J. Grady II, Rishi Khan, Ziyi Yin, and Felix J. Herrmann, “Large-scale parametric PDE approximations with model-parallel Fourier neural operators”, ML4SEISMIC Partners Meeting. 2023.
Richard Rex, Ziyi Yin, and Felix J. Herrmann, “Velocity Continuation for Common Image Gathers with Fourier Neural Operators”, in International Meeting for Applied Geoscience and Energy, 2024.
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Ali Siahkoohi, Mathias Louboutin, and Felix J. Herrmann, “Neural network augmented wave-equation simulation”, Georgia Institute of Technology, TR-CSE-2019-1, 2019.
Ali Siahkoohi, Rafael Orozco, Gabrio Rizzuti, Philipp A. Witte, Mathias Louboutin, and Felix J. Herrmann, “Multifidelity conditional normalizing flows for physics-guided Bayesian inference”, ML4SEISMIC Partners Meeting. 2021.
Ali Siahkoohi, Gabrio Rizzuti, Mathias Louboutin, and Felix J. Herrmann, “Unsupervised data-guided uncertainty analysis in imaging and horizon tracking”, in SIAM Texas-Louisiana, 2020.
Ali Siahkoohi, Chinen, M., Denton, T., W. Kleijn, B., and Skoglund, J., “Ultra-Low-Bitrate Speech Coding with Pretrained Transformers”, in Proceedings of INTERSPEECH, 2022.
Ali Siahkoohi, Gabrio Rizzuti, Philipp A. Witte, and Felix J. Herrmann, “Faster Uncertainty Quantification for Inverse Problems with Conditional Normalizing Flows”, Georgia Institute of Technology, TR-CSE-2020-2, 2020.
Ali Siahkoohi, Gabrio Rizzuti, and Felix J. Herrmann, “A deep-learning based Bayesian approach to seismic imaging and uncertainty quantification”, GT SEG Student Chapter. 2020.
Ali Siahkoohi, Mathias Louboutin, and Felix J. Herrmann, “The importance of transfer learning in seismic modeling and imaging”, Geophysics, 2019.
Ali Siahkoohi and Felix J. Herrmann, “Learning by example: fast reliability-aware seismic imaging with normalizing flows”, in SEG Technical Program Expanded Abstracts, 2021, pp. 1580-1585.
Ali Siahkoohi, “Deep generative models for solving geophysical inverse problems”, Georgia Institute of Technology, Atlanta, 2022.
Ali Siahkoohi, Gabrio Rizzuti, and Felix J. Herrmann, “A deep-learning based Bayesian approach to seismic imaging and uncertainty quantification”, in EAGE Annual Conference Proceedings, 2020.
Ali Siahkoohi, Gabrio Rizzuti, Rafael Orozco, and Felix J. Herrmann, “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.
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Philipp A. Witte, Mathias Louboutin, Ali Siahkoohi, Gabrio Rizzuti, Bas Peters, and Felix J. Herrmann, “InvertibleNetworks.jl - Memory efficient deep learning in Julia”, in JuliaCon, 2021.
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Ziyi Yin, Rafael Orozco, Ali Siahkoohi, Mathias Louboutin, and Felix J. Herrmann, “Uncertainty-aware time-lapse CO$_2$ monitoring with learned end-to-end inversion”, ML4SEISMIC Partners Meeting. 2022.
Ziyi Yin, Rafael Orozco, and Felix J. Herrmann, “WISER: multimodal variational inference for full-waveform inversion without dimensionality reduction”. 2024.
Ziyi Yin, “Introduction to Seismic Laboratory for Imaging and Modeling”, CSE Student Recruiting Event. 2023.
Ziyi Yin, Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “Generative AI for full-waveform variational inference”, Georgia Tech Geophysics Seminar. 2024.
Ziyi Yin, Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “WISER: full-Waveform variational Inference via Subsurface Extensions with Refinements”, in International Meeting for Applied Geoscience and Energy, 2024.
Ziyi Yin, Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “WISE: Full-waveform Inference with Subsurface Extensions”, ML4SEISMIC Partners Meeting. 2023.
Ziyi Yin, Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “Solving multiphysics-based inverse problems with learned surrogates and constraints”, Advanced Modeling and Simulation in Engineering Sciences, vol. 10, 2023.
Ziyi Yin, Ali Siahkoohi, Mathias Louboutin, and Felix J. Herrmann, “Learned coupled inversion for carbon sequestration monitoring and forecasting with Fourier neural operators”, in International Meeting for Applied Geoscience and Energy Expanded Abstracts, 2022.
Ziyi Yin, Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “WISE: full-Waveform variational Inference via Subsurface Extensions”, Geophysics, 2024.
Ziyi Yin, Rafael Orozco, Mathias Louboutin, Ali Siahkoohi, and Felix J. Herrmann, “Uncertainty-aware time-lapse monitoring of geological carbon storage with learned surrogates”, in Engineering Mechanics Institute Conference, 2023.

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