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Found 3 papers, 1 papers with code
Improving Explainability of Disentangled Representations using Multipath-Attribution Mappings
We propose a framework that utilizes interpretable disentangled representations for downstream-task prediction.
On maximum-likelihood estimation in the all-or-nothing regime
The result follows from two main technical points: (i) the connection established between the MLE and the MMSE, using the first and second-moment methods in the constrained signal space, (ii) a recovery regime for the MMSE stricter than the simple error vanishing characterization given in the standard AoN, that is here proved as a general result.
Statistical and computational thresholds for the planted $k$-densest sub-hypergraph problem
In this work, we consider the problem of recovery a planted $k$-densest sub-hypergraph on $d$-uniform hypergraphs.
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