Abstract: Recent diffusion models provide a promising zero-shot solution to noisy linear inverse problems without retraining for specific inverse problems. In this paper, we reveal that recent methods ...
Abstract: In this work, a hybrid forward-inverse neural network (HFINN) with a transceiver transformation module (TTM) is proposed to increase the generalizability of machine learning-based ...
Abstract: The Bayesian inference with prior knowledge has been proposed recently to solve the inverse problem in resonant ultrasound spectroscopy. It allows inferring the elastic properties of high ...
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