Biblio
Export 16 results:
Author Title Type [ Year
] Filters: Author is Huseyin Tuna Erdinc and Keyword is Summary Statistics [Clear All Filters]
, “Background-Conditioned Diffusion Inversion for Seismic Velocity Models”, in ML4SEISMIC Partners Meeting, 2025.
, “Context-aware Digital Twin for Underground Storage”, in Artificial Intelligence and Digital Twins for Earth Systems 2025, Austin, TX, 2025.
, “Context-Aware Digital Twin for Underground Storage Operations and Decision Making”, in Data Assimilation and Inverse Problems for Digital Twins Workshop 205, IMSI, Chicago, 2025.
, “Efficient and scalable posterior surrogate for seismic inversion via wavelet score-based generative models”, in International Meeting for Applied Geoscience and Energy, 2025.
, “Full-waveform variational inference with common-image gathers”, in International Meeting for Applied Geoscience and Energy, 2025.
, “Multiscale Wavelet Score-based Posterior Approximations for Seismic Inversion”, in ML4SEISMIC Partners Meeting, 2025.
, “Power-scaled Bayesian inference for velocity-model estimation”, in ML4SEISMIC Partners Meeting, 2025.
, “Power-scaled Bayesian inference with score-based generative models”, in International Meeting for Applied Geoscience and Energy, 2025.
, “SAGE — Subsurface foundational model with AI-driven Geostatistical Extraction”, in EAGE Workshop, 2025.
, “SAGE - Subsurface modeling with AI-driven Geostatistical Extraction and evaluation on North Sea Data”, in ML4SEISMIC Partners Meeting, 2025.
, “Sensitivity-aware rock physics enhanced digital shadow for underground-energy storage monitoring”, in International Meeting for Applied Geoscience and Energy, 2025.
, “Towards foundation models for subsurface priors and posteriors”, in Workshop on Scientific Machine Learning 2025, Austin, TX, 2025.
, “Digital Twins in the era of generative AI - Application to Geological CO2 Storage”, ICL Seminar. 2024.
, “Machine-learning enabled velocity-model building with uncertainty quantification”, ML4SEISMIC Partners Meeting. 2024.
, “SAGE – Subsurface foundational model with AI-driven Geostatical Extraction”, ML4SEISMIC Partners Meeting. 2024.
, “Inference of CO2 flow patterns – a feasibility study”, in Neural Information Processing Systems (NeurIPS), 2023.
