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2. Scalable interpretability via polynomials;dubey;Advances in Neural IInformation Processing Systems,2022
3. Understanding the difficulty of training deep feedforward neural networks;glorot;International Conference on Artificial Intelligence and Statistics (AISTATS),0
4. Dropblock: A regularization method for convolutional networks;ghiasi;ArXiv Preprint,2018
5. Controlling the complexity and lipschitz constant improves polynomial nets;zhu;International Conference on Learning Representations (ICLR),0