Dilip Krishnan
Dilip Krishnan
Research Scientist, Google
Verified email at google.com - Homepage
Cited by
Cited by
Deconvolutional networks
MD Zeiler, D Krishnan, GW Taylor, R Fergus
2010 IEEE Computer Society Conference on computer vision and pattern …, 2010
Fast image deconvolution using hyper-Laplacian priors
D Krishnan, R Fergus
Advances in neural information processing systems 22, 1033-1041, 2009
Unsupervised pixel-level domain adaptation with generative adversarial networks
K Bousmalis, N Silberman, D Dohan, D Erhan, D Krishnan
Proceedings of the IEEE conference on computer vision and pattern …, 2017
Blind deconvolution using a normalized sparsity measure
D Krishnan, T Tay, R Fergus
CVPR 2011, 233-240, 2011
Domain separation networks
K Bousmalis, G Trigeorgis, N Silberman, D Krishnan, D Erhan
arXiv preprint arXiv:1608.06019, 2016
Contrastive multiview coding
Y Tian, D Krishnan, P Isola
arXiv preprint arXiv:1906.05849, 2019
Restoring an image taken through a window covered with dirt or rain
D Eigen, D Krishnan, R Fergus
Proceedings of the IEEE international conference on computer vision, 633-640, 2013
Visualizing dataflow graphs of deep learning models in tensorflow
K Wongsuphasawat, D Smilkov, J Wexler, J Wilson, D Mane, D Fritz, ...
IEEE transactions on visualization and computer graphics 24 (1), 1-12, 2017
Supervised contrastive learning
P Khosla, P Teterwak, C Wang, A Sarna, Y Tian, P Isola, A Maschinot, ...
arXiv preprint arXiv:2004.11362, 2020
Contrastive representation distillation
Y Tian, D Krishnan, P Isola
arXiv preprint arXiv:1910.10699, 2019
Crisp boundary detection using pointwise mutual information
P Isola, D Zoran, D Krishnan, EH Adelson
European Conference on Computer Vision, 799-814, 2014
Reflection removal using ghosting cues
YC Shih, D Krishnan, F Durand, WT Freeman
Proceedings of the IEEE conference on computer vision and pattern …, 2015
What makes for good views for contrastive learning
Y Tian, C Sun, B Poole, D Krishnan, C Schmid, P Isola
arXiv preprint arXiv:2005.10243, 2020
Learning ordinal relationships for mid-level vision
D Zoran, P Isola, D Krishnan, WT Freeman
Proceedings of the IEEE International Conference on Computer Vision, 388-396, 2015
CAFE MOCHA: An Integrated Platform for Discovering Clinically Relevant Molecular Changes in Cancer—An Example of Distant Metastasis– and Recurrence …
NM Krishnan, M I, J Hariharan, B Panda
JCO clinical cancer informatics 2, 1-11, 2018
Large margin deep networks for classification
GF Elsayed, D Krishnan, H Mobahi, K Regan, S Bengio
arXiv preprint arXiv:1803.05598, 2018
Rethinking few-shot image classification: a good embedding is all you need?
Y Tian, Y Wang, D Krishnan, JB Tenenbaum, P Isola
arXiv preprint arXiv:2003.11539, 2020
Fantastic generalization measures and where to find them
Y Jiang, B Neyshabur, H Mobahi, D Krishnan, S Bengio
arXiv preprint arXiv:1912.02178, 2019
Adversarial robustness through local linearization
C Qin, J Martens, S Gowal, D Krishnan, K Dvijotham, A Fawzi, S De, ...
arXiv preprint arXiv:1907.02610, 2019
Synthesizing normalized faces from facial identity features
F Cole, D Belanger, D Krishnan, A Sarna, I Mosseri, WT Freeman
Proceedings of the IEEE conference on computer vision and pattern …, 2017
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