Titlebook: Advances in Intelligent Data Analysis XXII; 22nd International S Ioanna Miliou,Nico Piatkowski,Panagiotis Papapetro Conference proceedings

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Equivariant Parameter Sharing for?Porous Crystalline Materials978-3-662-13380-4

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https://doi.org/10.1007/978-1-349-19471-1 the comparability rate. We illustrate the deployment of the protocol on six datasets, arriving at some conclusions that deviate from conclusions from (mutually disagreeing) existing literature, and showing how individual steps in the protocol each have their role to play in arriving at a final postulate.

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https://doi.org/10.1007/978-3-642-58274-5rforms two self-supervised baselines across multiple data sets and scenarios. Crucially, this includes conditions in which only a small amount of labeled data is available. Empirically, the Siamese component has more impact, but the denoising autoencoder is nevertheless necessary to improve performance.

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0302-9743 d and selected from 94 submissions. IDA is an international symposium presenting advances in the intelligent?analysis of data. Distinguishing characteristics of IDA are its focus on novel, inspiring ideas, its focus on research, and its relatively small scale.?..?.978-3-031-58546-3978-3-031-58547-0Series ISSN 0302-9743 Series E-ISSN 1611-3349

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