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University of Cambridge
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By rethinking hypothesis generation as a sampling problem, this framework boosts both the quality and diversity of scientific hypotheses, challenging the status quo of optimization-focused methods.
By intelligently fusing Wiener Chaos Expansion with Neural Operators, this new method cracks the notoriously difficult problem of simulating singular stochastic PDEs without relying on computationally expensive renormalization techniques.
