| Visualizing and understanding convolutional networks MD Zeiler, R Fergus European conference on computer vision, 818-833, 2014 | 15998 | 2014 |
| Adadelta: an adaptive learning rate method MD Zeiler arXiv preprint arXiv:1212.5701, 2012 | 6908 | 2012 |
| Regularization of neural networks using dropconnect L Wan, M Zeiler, S Zhang, Y Le Cun, R Fergus International conference on machine learning, 1058-1066, 2013 | 2679 | 2013 |
| Deconvolutional networks MD Zeiler, D Krishnan, GW Taylor, R Fergus Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on …, 2010 | 1763 | 2010 |
| Adaptive deconvolutional networks for mid and high level feature learning MD Zeiler, GW Taylor, R Fergus 2011 international conference on computer vision, 2018-2025, 2011 | 1404 | 2011 |
| Stochastic pooling for regularization of deep convolutional neural networks MD Zeiler, R Fergus arXiv preprint arXiv:1301.3557, 2013 | 1126 | 2013 |
| On rectified linear units for speech processing MD Zeiler, M Ranzato, R Monga, M Mao, K Yang, QV Le, P Nguyen, ... 2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013 | 629 | 2013 |
| Adadelta: An adaptive learning rate method. arXiv 2012 MD Zeiler arXiv preprint arXiv:1212.5701 1212, 2012 | 173 | 2012 |
| Computer vision–ECCV 2014 MD Zeiler, R Fergus, D Fleet, T Pajdla, B Schiele, T Tuytelaars Lecture Notes in Computer Science 8689, 818-833, 2014 | 119 | 2014 |
| ADADELTA: an adaptive learning rate method. arXiv MD Zeiler arXiv preprint arXiv:1212.5701 22, 2012 | 116 | 2012 |
| European conference on computer vision MD Zeiler, R Fergus Visualizing and understanding convolutional networks, 818-833, 2014 | 107 | 2014 |
| Hierarchical convolutional deep learning in computer vision MD Zeiler New York University, 2013 | 82 | 2013 |
| Visualizing and understanding convolutional networks (2013) MD Zeiler, R Fergus arXiv preprint arXiv:1311.2901, 2013 | 66 | 2013 |
| FERGUSR MD Zeiler VisualizingandunderstandingconvG olutionalnetworks, 2014 | 57 | 2014 |
| Facial expression transfer with input-output temporal restricted boltzmann machines M Zeiler, GW Taylor, L Sigal, I Matthews, R Fergus Advances in neural information processing systems 24, 2011 | 42 | 2011 |
| Stochastic pooling for regularization of deep convolutional neural networks. arXiv MD Zeiler, R Fergus arXiv preprint arXiv:1301.3557, 2013 | 21 | 2013 |
| Modeling pigeon behavior using a Conditional Restricted Boltzmann Machine. MD Zeiler, GW Taylor, NF Troje, GE Hinton ESANN, 2009 | 21 | 2009 |
| Differentiable pooling for hierarchical feature learning MD Zeiler, R Fergus arXiv preprint arXiv:1207.0151, 2012 | 15 | 2012 |
| Proceedings of the 30th International Conference on Machine Learning (ICML-13) L Wan, M Zeiler, S Zhang, YL Cun, R Fergus JMLR Workshop and Conference Proceedings, 2013 | 10 | 2013 |
| Learning image decompositions with hierarchical sparse coding M Zeiler, R Fergus Tech. Rep. TR2010-935, 2010 | 9 | 2010 |
Rob FergusResearch Scientist, DeepMind. Professor of Computer Science, New York UniversityVerified email at cs.nyu.edu
