Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs).

Articles citing Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs).

Title / Author	Year
Identity mappings in deep residual networks K He, X Zhang, S Ren, J Sun European conference on computer vision, 630-645	2016
Xception: Deep learning with depthwise separable convolutions F Chollet Proceedings of the IEEE conference on computer vision and pattern …	2017
Wide residual networks S Zagoruyko, N Komodakis arXiv preprint arXiv:1605.07146	2016
Towards evaluating the robustness of neural networks N Carlini, D Wagner 2017 ieee symposium on security and privacy (sp), 39-57	2017
Graph attention networks P Veličković, G Cucurull, A Casanova, A Romero, P Lio, Y Bengio arXiv preprint arXiv:1710.10903	2017
Learning transferable architectures for scalable image recognition B Zoph, V Vasudevan, J Shlens, QV Le Proceedings of the IEEE conference on computer vision and pattern …	2018
Gans trained by a two time-scale update rule converge to a local nash equilibrium M Heusel, H Ramsauer, T Unterthiner, B Nessler, S Hochreiter Advances in neural information processing systems, 6626-6637	2017
Recent advances in convolutional neural networks J Gu, Z Wang, J Kuen, L Ma, A Shahroudy, B Shuai, T Liu, X Wang, ... Pattern Recognition 77, 354-377	2018
Unsupervised monocular depth estimation with left-right consistency C Godard, O Mac Aodha, GJ Brostow Proceedings of the IEEE Conference on Computer Vision and Pattern …	2017
Efficient processing of deep neural networks: A tutorial and survey V Sze, YH Chen, TJ Yang, JS Emer Proceedings of the IEEE 105 (12), 2295-2329	2017
Self-normalizing neural networks G Klambauer, T Unterthiner, A Mayr, S Hochreiter Advances in neural information processing systems, 971-980	2017
Improved variational inference with inverse autoregressive flow DP Kingma, T Salimans, R Jozefowicz, X Chen, I Sutskever, M Welling Advances in neural information processing systems, 4743-4751	2016
Began: Boundary equilibrium generative adversarial networks D Berthelot, T Schumm, L Metz arXiv preprint arXiv:1703.10717	2017
Curiosity-driven exploration by self-supervised prediction D Pathak, P Agrawal, AA Efros, T Darrell Proceedings of the IEEE Conference on Computer Vision and Pattern …	2017
f-gan: Training generative neural samplers using variational divergence minimization S Nowozin, B Cseke, R Tomioka Advances in neural information processing systems, 271-279	2016
Deep convolutional neural networks for image classification: A comprehensive review W Rawat, Z Wang Neural computation 29 (9), 2352-2449	2017
Designing neural network architectures using reinforcement learning B Baker, O Gupta, N Naik, R Raskar arXiv preprint arXiv:1611.02167	2016
Deep learning with convolutional neural networks for EEG decoding and visualization RT Schirrmeister, JT Springenberg, LDJ Fiederer, M Glasstetter, ... Human brain mapping 38 (11), 5391-5420	2017
Deep sets M Zaheer, S Kottur, S Ravanbakhsh, B Poczos, RR Salakhutdinov, ... Advances in neural information processing systems, 3391-3401	2017
Searching for activation functions P Ramachandran, B Zoph, QV Le arXiv preprint arXiv:1710.05941	2017

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