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Ross Goroshin
Ross Goroshin
Google Brain
在 google.com 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Efficient object localization using convolutional networks
J Tompson, R Goroshin, A Jain, Y LeCun, C Bregler
Proceedings of the IEEE conference on computer vision and pattern …, 2015
13542015
Learning to navigate in complex environments
P Mirowski, R Pascanu, F Viola, H Soyer, AJ Ballard, A Banino, M Denil, ...
arXiv preprint arXiv:1611.03673, 2016
7662016
Vector-based navigation using grid-like representations in artificial agents
A Banino, C Barry, B Uria, C Blundell, T Lillicrap, P Mirowski, A Pritzel, ...
Nature 557 (7705), 429-433, 2018
4772018
Meta-dataset: A dataset of datasets for learning to learn from few examples
E Triantafillou, T Zhu, V Dumoulin, P Lamblin, U Evci, K Xu, R Goroshin, ...
arXiv preprint arXiv:1903.03096, 2019
3862019
Stacked What-Where Auto-encoders
J Zhao, M Mathieu, R Goroshin, Y LeCun
https://arxiv.org/abs/1506.02351, 2016
3262016
Unsupervised learning of spatiotemporally coherent metrics
R Goroshin, J Bruna, J Tompson, D Eigen, Y LeCun
Proceedings of the IEEE international conference on computer vision, 4086-4093, 2015
1452015
Unsupervised learning of spatiotemporally coherent metrics
R Goroshin, J Bruna, J Tompson, D Eigen, Y LeCun
Proceedings of the IEEE international conference on computer vision, 4086-4093, 2015
1452015
Learning to linearize under uncertainty
R Goroshin, MF Mathieu, Y LeCun
Advances in neural information processing systems 28, 2015
1242015
Saturating auto-encoders
R Goroshin, Y LeCun
arXiv preprint arXiv:1301.3577, 2013
552013
Unsupervised feature learning from temporal data
R Goroshin, J Bruna, J Tompson, D Eigen, Y LeCun
arXiv preprint arXiv:1504.02518, 2015
492015
Stacked whatwhere auto-encoders
J Zhao, M Mathieu, R Goroshin, Y Lecun
arXiv preprint arXiv:1506.02351, 2015
292015
Approximate solutions to several visibility optimization problems
R Goroshin, Q Huynh, HM Zhou
Communications in Mathematical Sciences 9 (2), 535-550, 2011
222011
An effective anti-aliasing approach for residual networks
C Vasconcelos, H Larochelle, V Dumoulin, NL Roux, R Goroshin
arXiv preprint arXiv:2011.10675, 2020
192020
Comparing transfer and meta learning approaches on a unified few-shot classification benchmark
V Dumoulin, N Houlsby, U Evci, X Zhai, R Goroshin, S Gelly, H Larochelle
arXiv preprint arXiv:2104.02638, 2021
142021
Learning to navigate in complex environments. arXiv
P Mirowski, R Pascanu, F Viola, H Soyer, AJ Ballard, A Banino, M Denil, ...
arXiv preprint arXiv:1611.03673, 2016
92016
Impact of aliasing on generalization in deep convolutional networks
C Vasconcelos, H Larochelle, V Dumoulin, R Romijnders, N Le Roux, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
82021
Automated cable tracking in sonar imagery
JC Isaacs, R Goroshin
OCEANS 2010 MTS/IEEE SEATTLE, 1-7, 2010
72010
Efficient object localization using convolutional networks. CoRR abs/1411.4280 (2014)
J Tompson, R Goroshin, A Jain, Y LeCun, C Bregler
arXiv preprint arXiv:1411.4280, 2014
42014
Code for" Meta-dataset: A dataset of datasets for learning to learn from few examples
E Triantafillou, T Zhu, V Dumoulin, P Lamblin, K Xu, R Goroshin, ...
32019
Obstacle detection using a monocular camera
R Goroshin
Georgia Institute of Technology, 2008
32008
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