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| | newhistoryofknowledge.com
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| | The editors invite contributions to Vol. 5 of the scholarly yearbookHistory of Intellectual Culture(De Gruyter), to be published in autumn 2026. The contributions will be peer reviewed and available open access. The deadline for submitting a proposal is 5 May. See this document for more information: HIC_CfP_Vol5_2026Download Photo byVojtech BruzekonUnsplash
| | internationaljournalofwellbeing.org
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| | www.leibniz-gemeinschaft.de
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| | www.paepper.com
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| Today's paper: Rethinking 'Batch' in BatchNorm by Wu & Johnson BatchNorm is a critical building block in modern convolutional neural networks. Its unique property of operating on "batches" instead of individual samples introduces significantly different behaviors from most other operations in deep learning. As a result, it leads to many hidden caveats that can negatively impact model's performance in subtle ways. This is a citation from the paper's abstract and the emphasis is mine which caught my attention. Let's explore these subtle ways which can negatively impact your model's performance! The paper of Wu & Johnson can be found on arxiv.