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2022
Rafael Orozco, Mathias Louboutin, Ali Siahkoohi, Gabrio Rizzuti, and Felix J. Herrmann, “Adjoint operators as summary functions in amortized Bayesian inference frameworks”, ML4SEISMIC Partners Meeting. 2022.
Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “Normalizing flows for regularization of 3D seismic inverse problems”, ML4SEISMIC Partners Meeting. 2022.
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.
2023
Rafael Orozco, Ali Siahkoohi, Gabrio Rizzuti, Tristan van Leeuwen, and Felix J. Herrmann, “Adjoint operators enable fast and amortized machine learning based Bayesian uncertainty quantification”, in SPIE Medical Imaging Conference, 2023.
Abhinav Prakash Gahlot, Huseyin Tuna Erdinc, Rafael Orozco, Ziyi Yin, and Felix J. Herrmann, “Inference of CO2 flow patterns – a feasibility study”, in Neural Information Processing Systems (NeurIPS), 2023.
Abhinav Prakash Gahlot, Ting-ying Yu, Rafael Orozco, Ziyi Yin, Mathias Louboutin, and Felix J. Herrmann, “Monitoring subsurface CO2 plumes with learned sequential Bayesian inference”, ML4SEISMIC Partners Meeting. 2023.
Ting-ying Yu, Abhinav Prakash Gahlot, Rafael Orozco, Ziyi Yin, Mathias Louboutin, and Felix J. Herrmann, “Monitoring Subsurface CO2 Plumes with Sequential Bayesian Inference”, in International Meeting for Applied Geoscience and Energy, 2023.
Rafael Orozco, Ali Siahkoohi, Mathias Louboutin, and Felix J. Herrmann, “Refining Amortized Posterior Approximations using Gradient-Based Summary Statistics”, in 5th Symposium on Advances in Approximate Bayesian Inference, 2023.
2024
Rafael Orozco, Abhinav Prakash Gahlot, and Felix J. Herrmann, “BEACON: Bayesian Experimental design Acceleration with Conditional Normalizing flows - a case study in optimal monitor well placement for CO2 sequestration”, in International Meeting for Applied Geoscience and Energy, 2024.
Abhinav Prakash Gahlot, Haoyun Li, Ziyi Yin, Rafael Orozco, and Felix J. Herrmann, “A Digital Twin for Geological Carbon Storage with Controlled Injectivity”, in International Meeting for Applied Geoscience and Energy, 2024.
Abhinav Prakash Gahlot, Haoyun Li, Ziyi Yin, Rafael Orozco, and Felix J. Herrmann, “A Digital Twin for Geological Carbon Storage with Controlled Injectivity”, ML4SEISMIC Partners Meeting. 2024.
Abhinav Prakash Gahlot, Rafael Orozco, Haoyun Li, Huseyin Tuna Erdinc, Ziyi Yin, Mathias Louboutin, and Felix J. Herrmann, “Digital Twins in the era of generative AI - Application to Geological CO2 Storage”, ICL Seminar. 2024.
Abhinav Prakash Gahlot, Rafael Orozco, Haoyun Li, Huseyin Tuna Erdinc, Ziyi Yin, Mathias Louboutin, and Felix J. Herrmann, “Digital Twins in the Era of Generative AI: Application to Geological CO2 Storage”, HCMF Seminar. 2024.
Abhinav Prakash Gahlot, Rafael Orozco, Haoyun Li, Huseyin Tuna Erdinc, Ziyi Yin, Mathias Louboutin, and Felix J. Herrmann, “Digital Twins in the era of generative AI — Application to Geological CO2 Storage”, in ICON Seminar in IoT, 2024.
Abhinav Prakash Gahlot, Rafael Orozco, Haoyun Li, Huseyin Tuna Erdinc, Ziyi Yin, Mathias Louboutin, and Felix J. Herrmann, “DT4GCS — Digital Twin for Geological CO2 Storage and Control”, in Geophysical Research for Gigatonnes CO2 Storage, Colorado School of Mines, 2024.
Felix J. Herrmann, Abhinav Prakash Gahlot, Rafael Orozco, Ziyi Yin, and Haoyun Li, “DT4GCS –- Digital Twin for Geological CO2 Storage and Control”, in Gigatonnes CO2 Storage Workshop, 2024.
Yunlin Zeng, Rafael Orozco, Ziyi Yin, and Felix J. Herrmann, “Enhancing Full-Waveform Variational Inference through Stochastic Resampling and Data Augmentation”, in International Meeting for Applied Geoscience and Energy, 2024.
Yunlin Zeng, Ziyi Yin, Rafael Orozco, Mathias Louboutin, and Felix J. Herrmann, “Enhancing Full-Waveform Variational Inference through Stochastic Resampling”, ML4SEISMIC Partners Meeting. 2024.
Rafael Orozco, “GENERATIVE MODELS FOR UNCERTAINTY QUANTIFICATION OF MEDICAL AND SEISMIC IMAGING”, Georgia Institute of Technology, Atlanta, 2024.
Rafael Orozco, Philipp A. Witte, Mathias Louboutin, Ali Siahkoohi, Gabrio Rizzuti, Bas Peters, and Felix J. Herrmann, “InvertibleNetworks.jl: A Julia package for scalable normalizing flows”, Journal of Open Source Software, vol. 9, 2024.
Rafael Orozco, Huseyin Tuna Erdinc, Souza, T., Yunlin Zeng, Ziyi Yin, and Felix J. Herrmann, “Machine-learning enabled velocity-model building with uncertainty quantification”, ML4SEISMIC Partners Meeting. 2024.
Rafael Orozco, Ziyi Yin, Ali Siahkoohi, Mathias Louboutin, and Felix J. Herrmann, “Neural wave-based imaging with amortized uncertainty quantification”, in Inverse Problems: Modelling and Simulation, 2024.
Rafael Orozco, Ziyi Yin, Ali Siahkoohi, Mathias Louboutin, and Felix J. Herrmann, “Neural wave-based imaging with amortized uncertainty quantification”, ICL Seminar. 2024.
Rafael Orozco, Abhinav Prakash Gahlot, Peng Chen, Mathias Louboutin, and Felix J. Herrmann, “Normalizing Flows for Bayesian Experimental Design in Imaging Applications”, in EAGE Annual Conference Proceedings, 2024.
Z. Deng, Rafael Orozco, Abhinav Prakash Gahlot, and Felix J. Herrmann, “Probabilistic Joint Recovery Method for CO2 plume monitoring”, ML4SEISMIC Partners Meeting. 2024.

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