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Scale-covariant and scale-invariant Gaussian derivative networks. https://t.co/fFdqv3SOTN
Scale-covariant and scale-invariant Gaussian derivative networks. https://t.co/fFdqv3SOTN
Alexander Köhler, Michael Breuß: Towards Efficient Time Stepping for Numerical Shape Correspondence https://t.co/5prBIj7uLp https://t.co/IBmSiOku8j
RT @StatMLPapers: CLIP: Cheap Lipschitz Training of Neural Networks. (arXiv:2103.12531v2 [cs.LG] UPDATED) https://t.co/e0ZjKhotTX
RT @StatMLPapers: CLIP: Cheap Lipschitz Training of Neural Networks. (arXiv:2103.12531v2 [cs.LG] UPDATED) https://t.co/e0ZjKhotTX