Striving for Simplicity: The All Convolutional Net.

Articles citing Striving for Simplicity: The All Convolutional Net.

Title / Author	Year
Densely connected convolutional networks G Huang, Z Liu, L Van Der Maaten, KQ Weinberger Proceedings of the IEEE conference on computer vision and pattern …	2017
Unsupervised representation learning with deep convolutional generative adversarial networks A Radford, L Metz, S Chintala arXiv preprint arXiv:1511.06434	2015
Identity mappings in deep residual networks K He, X Zhang, S Ren, J Sun European conference on computer vision, 630-645	2016
A survey on deep learning in medical image analysis G Litjens, T Kooi, BE Bejnordi, AAA Setio, F Ciompi, M Ghafoorian, ... Medical image analysis 42, 60-88	2017
Fast and accurate deep network learning by exponential linear units (elus) DA Clevert, T Unterthiner, S Hochreiter arXiv preprint arXiv:1511.07289	2015
Towards evaluating the robustness of neural networks N Carlini, D Wagner 2017 ieee symposium on security and privacy (sp), 39-57	2017
Grad-cam: Visual explanations from deep networks via gradient-based localization RR Selvaraju, M Cogswell, A Das, R Vedantam, D Parikh, D Batra Proceedings of the IEEE international conference on computer vision, 618-626	2017
V-net: Fully convolutional neural networks for volumetric medical image segmentation F Milletari, N Navab, SA Ahmadi 2016 fourth international conference on 3D vision (3DV), 565-571	2016
Neural architecture search with reinforcement learning B Zoph, QV Le arXiv preprint arXiv:1611.01578	2016
Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation K Kamnitsas, C Ledig, VFJ Newcombe, JP Simpson, AD Kane, DK Menon, ... Medical image analysis 36, 61-78	2017
Training very deep networks RK Srivastava, K Greff, J Schmidhuber Advances in neural information processing systems, 2377-2385	2015
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
Geometric deep learning: going beyond euclidean data MM Bronstein, J Bruna, Y LeCun, A Szlam, P Vandergheynst IEEE Signal Processing Magazine 34 (4), 18-42	2017
NIPS 2016 tutorial: Generative adversarial networks I Goodfellow arXiv preprint arXiv:1701.00160	2016
Deep networks with stochastic depth G Huang, Y Sun, Z Liu, D Sedra, KQ Weinberger European conference on computer vision, 646-661	2016
Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling J Wu, C Zhang, T Xue, B Freeman, J Tenenbaum Advances in neural information processing systems, 82-90	2016
Semi-supervised learning with ladder networks A Rasmus, M Berglund, M Honkala, H Valpola, T Raiko Advances in neural information processing systems, 3546-3554	2015
Weight normalization: A simple reparameterization to accelerate training of deep neural networks T Salimans, DP Kingma Advances in neural information processing systems, 901-909	2016
mixup: Beyond empirical risk minimization H Zhang, M Cisse, YN Dauphin, D Lopez-Paz arXiv preprint arXiv:1710.09412	2017
Understanding black-box predictions via influence functions PW Koh, P Liang arXiv preprint arXiv:1703.04730	2017

1 - 20

Dates and citation counts are estimated and are determined automatically by a computer program.