متابعة
Roger Grosse
Roger Grosse
Associate Professor, University of Toronto
بريد إلكتروني تم التحقق منه على cs.toronto.edu - الصفحة الرئيسية
عنوان
عدد مرات الاقتباسات
عدد مرات الاقتباسات
السنة
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations‏
H Lee, R Grosse, R Ranganath, AY Ng‏
International Conference on Machine Learning, 609-616, 2009‏
34982009
Isolating sources of disentanglement in variational autoencoders‏
RTQ Chen, X Li, RB Grosse, DK Duvenaud‏
Advances in neural information processing systems 31, 2018‏
15462018
Importance weighted autoencoders‏
Y Burda, R Grosse, R Salakhutdinov‏
arXiv preprint arXiv:1509.00519, 2015‏
15052015
Optimizing neural networks with kronecker-factored approximate curvature‏
J Martens, R Grosse‏
International conference on machine learning, 2408-2417, 2015‏
11672015
Scalable trust-region method for deep reinforcement learning using kronecker-factored approximation‏
Y Wu, E Mansimov, RB Grosse, S Liao, J Ba‏
Advances in neural information processing systems 30, 2017‏
8592017
Picking winning tickets before training by preserving gradient flow‏
C Wang, G Zhang, R Grosse‏
arXiv preprint arXiv:2002.07376, 2020‏
7312020
Structure discovery in nonparametric regression through compositional kernel search‏
D Duvenaud, J Lloyd, R Grosse, J Tenenbaum, G Zoubin‏
International Conference on Machine Learning, 1166-1174, 2013‏
6552013
The reversible residual network: Backpropagation without storing activations‏
AN Gomez, M Ren, R Urtasun, RB Grosse‏
Advances in neural information processing systems 30, 2017‏
6302017
Ground truth dataset and baseline evaluations for intrinsic image algorithms‏
R Grosse, MK Johnson, EH Adelson, WT Freeman‏
International Conference on Computer Vision, 2335-2342, 2009‏
5502009
Unsupervised learning of hierarchical representations with convolutional deep belief networks‏
H Lee, R Grosse, R Ranganath, AY Ng‏
Communications of the ACM 54 (10), 95-103, 2011‏
5272011
Flipout: Efficient pseudo-independent weight perturbations on mini-batches‏
Y Wen, P Vicol, J Ba, D Tran, R Grosse‏
arXiv preprint arXiv:1803.04386, 2018‏
4002018
Sorting out Lipschitz function approximation‏
C Anil, J Lucas, R Grosse‏
International conference on machine learning, 291-301, 2019‏
3902019
Shift-invariant sparse coding for audio classification‏
R Grosse, R Raina, H Kwong, AY Ng‏
Uncertainty in AI, 2007‏
356*2007
Functional variational Bayesian neural networks‏
S Sun, G Zhang, J Shi, R Grosse‏
arXiv preprint arXiv:1903.05779, 2019‏
3172019
Three mechanisms of weight decay regularization‏
G Zhang, C Wang, B Xu, R Grosse‏
arXiv preprint arXiv:1810.12281, 2018‏
3042018
A kronecker-factored approximate fisher matrix for convolution layers‏
R Grosse, J Martens‏
International Conference on Machine Learning, 573-582, 2016‏
3002016
Automatic construction and natural-language description of nonparametric regression models‏
J Lloyd, D Duvenaud, R Grosse, J Tenenbaum, Z Ghahramani‏
Proceedings of the AAAI Conference on Artificial Intelligence 28 (1), 2014‏
2942014
On the quantitative analysis of decoder-based generative models‏
Y Wu, Y Burda, R Salakhutdinov, R Grosse‏
arXiv preprint arXiv:1611.04273, 2016‏
2822016
Noisy natural gradient as variational inference‏
G Zhang, S Sun, D Duvenaud, R Grosse‏
International conference on machine learning, 5852-5861, 2018‏
2572018
Discovering language model behaviors with model-written evaluations‏
E Perez, S Ringer, K Lukosiute, K Nguyen, E Chen, S Heiner, C Pettit, ...‏
Findings of the Association for Computational Linguistics: ACL 2023, 13387-13434, 2023‏
2502023
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مقالات 1–20