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Predicting unreliable predictions by shattering a neural network

X. Ji, R. Pascanu, D. Hjelm, A. Vedaldi, B. Lakshminarayanan, and Y. Bengio. arXiv preprint arXiv:2106.08365, (2021)

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Boundary-Seeking Generative Adversarial NetworksR. Hjelm, A. Jacob, T. Che, A. Trischler, K. Cho, and Y. Bengio. (2017)cite arxiv:1702.08431.Evolving Culture Versus Local Minima.Y. Bengio. Growing Adaptive Machines, volume 557 of Studies in Computational Intelligence, Springer, (2014)Support vector machines for improving the classification of brain PET images.M. Bonneville, J. Meunier, Y. Bengio, and J. Soucy. Medical Imaging: Image Processing, volume 3338 of SPIE Proceedings, SPIE, (1998)DNN's Sharpest Directions Along the SGD TrajectoryS. Jastrzębski, Z. Kenton, N. Ballas, A. Fischer, Y. Bengio, and A. Storkey. (2018)Feedforward Initialization for Fast Inference of Deep Generative Networks is biologically plausible.Y. Bengio, B. Scellier, O. Bilaniuk, J. Sacramento, and W. Senn. CoRR, (2016)A3T: Adversarially Augmented Adversarial Training.A. Erraqabi, A. Baratin, Y. Bengio, and S. Lacoste-Julien. CoRR, (2018)Dendritic error backpropagation in deep cortical microcircuits.J. Sacramento, R. Costa, Y. Bengio, and W. Senn. CoRR, (2018)A Walk with SGD.C. Xing, D. Arpit, C. Tsirigotis, and Y. Bengio. CoRR, (2018)An empirical evaluation of deep architectures on problems with many factors of variation.H. Larochelle, D. Erhan, A. Courville, J. Bergstra, and Y. Bengio. ICML, volume 227 of ACM International Conference Proceeding Series, page 473-480. ACM, (2007)Curriculum learning.Y. Bengio, J. Louradour, R. Collobert, and J. Weston. ICML, volume 382 of ACM International Conference Proceeding Series, page 41-48. ACM, (2009)

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Predicting unreliable predictions by shattering a neural network

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Predicting unreliable predictions by shattering a neural network

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Predicting unreliable predictions by shattering a neural network