HDFM adds a continuous heat-dissipation (blur) process to flow matching, aligns an interpolated path to fix ill-posed inverse heat dissipation, and uses x-prediction to ease high-dimensional regression, yielding better performance than most baselines on image datasets.
IEEE Transactions on Pattern Analysis and Machine Intelligence , year=
2 Pith papers cite this work. Polarity classification is still indexing.
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DAPPr projects a possibilistic posterior over network parameters to predictions using supremum operators and approximates it with learnable Dirichlet functions to yield an efficient training objective for epistemic uncertainty.
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