most citedA Framework for Building Enviromics Matrices in Mixed Models

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cs.LG2024★ 18 cited

Croissant: A Metadata Format for ML-Ready Datasets

Mubashara Akhtar, Omar Benjelloun, Costanza Conforti +28

Data is a critical resource for machine learning (ML), yet working with data remains a key friction point. This paper introduces Croissant, a metadata format for datasets that crea…

cs.LG2020★ 1 cited

Gini in a Bottleneck: Sparse Molecular Representations for Graph Convolutional Neural Networks

Ryan Henderson, Djork-Arné Clevert, Floriane Montanari

Due to the nature of deep learning approaches, it is inherently difficult to understand which aspects of a molecular graph drive the predictions of the network. As a mitigation str…