Unsupervised latent space alignment with hyperspherical geodesic matching
Read the original at arxiv.org→arXiv:2608.28840v1 Announce Type: new Abstract: Independently trained neural networks tend to encode the same data with similar latent geometries. These latent geometries are not directly compatible, yet they can be...
Original headline: "Unsupervised Latent Space Alignment with Hyperspherical Geodesic Matching"
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- Sep 1, 04:00 UTC arXiv cs.LG lead source Unsupervised Latent Space Alignment with Hyperspherical Geodesic Matching