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cs.DC2026
Multi-Dataset Inverse Problem Solving with Distributed Generative AI
Daniel Lersch, Steven Goldenberg, Johann Rudi +5
Extracting a shared set of unknown, not directly measurable quantities from multiple, heterogeneous datasets is a common challenge across scientific domains. A prominent example is…
cs.DC2024
SAGIPS: A Scalable Asynchronous Generative Inverse Problem Solver
Daniel Lersch, Malachi Schram, Zhenyu Dai +4
Large scale, inverse problem solving deep learning algorithms have become an essential part of modern research and industrial applications. The complexity of the underlying inverse…