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              <p>To implement convex functions with neural networks, the standard way is to use Input Convex Neural Networks (ICNNs). This article provides a study of their expressivity, theoretically and experimentally. Leveraging the characterization of convex ReLU networks, we introduce a new regularisation which softly enforces convexity of the learnt function.</p>
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