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School of Mathematics, Southeast University
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Transforming edge posteriors from diffuse uncertainty into structured clarity, Diff-prior revolutionizes how we infer interaction graphs in complex systems.
Unlock interpretable and reliable predictions for ultra-large complex systems, like climate patterns, by inferring governing equations at scales previously inaccessible.
Achieve state-of-the-art dynamic link prediction by fusing temporal-frequency analysis with wavelet decomposition in a novel Transformer architecture, outperforming existing methods by significant margins.
