Impulse responses are cast as random atomic superpositions of stable poles inside a disk and recovered through constrained convex optimization that encodes engineering priors.
Journal of Machine Learning Research , volume=
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
RDM trains one-step generators via MMD on large batches and multi-encoder representations, achieving SOTA SW_r14 of 1.30 on ImageNet and distilling FLUX.2 to one-step with gains on GenEval and PickScore.
citing papers explorer
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Randomized Atomic Feature Models for Physics-Informed Identification of Dynamic Systems
Impulse responses are cast as random atomic superpositions of stable poles inside a disk and recovered through constrained convex optimization that encodes engineering priors.
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Representation Distribution Matching for One-Step Visual Generation
RDM trains one-step generators via MMD on large batches and multi-encoder representations, achieving SOTA SW_r14 of 1.30 on ImageNet and distilling FLUX.2 to one-step with gains on GenEval and PickScore.