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Identifying circular orders for blobs in phylogenetic networks
We consider the identifiability of the circular order in which subnetworks attach to a blob, first proving that this order is well-defined for outer-labeled planar blobs.
Measuring and Mitigating Local Instability in Deep Neural Networks
We formulate the model stability problem by studying how the predictions of a model change, even when it is retrained on the same data, as a consequence of stochasticity in the training process.
Identifiability of local and global features of phylogenetic networks from average distances
We propose the "distance split tree", which can be constructed from pairwise distances, and prove that it is a refinement of the network's tree of blobs, capturing the tree-like features of the network.
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