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Co-advise: Cross Inductive Bias Distillation


Jun 23, 2021
Sucheng Ren, Zhengqi Gao, Tianyu Hua, Zihui Xue, Yonglong Tian, Shengfeng He, Hang Zhao


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Simple Distillation Baselines for Improving Small Self-supervised Models


Jun 21, 2021
Jindong Gu, Wei Liu, Yonglong Tian


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Generative Models as a Data Source for Multiview Representation Learning


Jun 09, 2021
Ali Jahanian, Xavier Puig, Yonglong Tian, Phillip Isola


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Divide and Contrast: Self-supervised Learning from Uncurated Data


May 17, 2021
Yonglong Tian, Olivier J. Henaff, Aaron van den Oord


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Composable Augmentation Encoding for Video Representation Learning


Apr 01, 2021
Chen Sun, Arsha Nagrani, Yonglong Tian, Cordelia Schmid


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Information-Preserving Contrastive Learning for Self-Supervised Representations


Dec 17, 2020
Tianhong Li, Lijie Fan, Yuan Yuan, Hao He, Yonglong Tian, Dina Katabi

* The first two authors contributed equally to this paper 

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What makes for good views for contrastive learning


May 20, 2020
Yonglong Tian, Chen Sun, Ben Poole, Dilip Krishnan, Cordelia Schmid, Phillip Isola

* submitted to ECCV 2020 

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Supervised Contrastive Learning


Apr 23, 2020
Prannay Khosla, Piotr Teterwak, Chen Wang, Aaron Sarna, Yonglong Tian, Phillip Isola, Aaron Maschinot, Ce Liu, Dilip Krishnan


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Rethinking Few-Shot Image Classification: a Good Embedding Is All You Need?


Mar 25, 2020
Yonglong Tian, Yue Wang, Dilip Krishnan, Joshua B. Tenenbaum, Phillip Isola

* First two authors contributed equally. Code: http://github.com/WangYueFt/rfs/ 

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Contrastive Representation Distillation


Oct 23, 2019
Yonglong Tian, Dilip Krishnan, Phillip Isola

* Project Page: http://hobbitlong.github.io/CRD/, Code: http://github.com/HobbitLong/RepDistiller 

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Training-Free Uncertainty Estimation for Neural Networks


Sep 28, 2019
Lu Mi, Hao Wang, Yonglong Tian, Nir Shavit

* 15 pages, 10 figures 

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Contrastive Multiview Coding


Jun 23, 2019
Yonglong Tian, Dilip Krishnan, Phillip Isola

* In submission. Code: http://github.com/HobbitLong/CMC/ 

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Learning to Infer and Execute 3D Shape Programs


Jan 09, 2019
Yonglong Tian, Andrew Luo, Xingyuan Sun, Kevin Ellis, William T. Freeman, Joshua B. Tenenbaum, Jiajun Wu

* ICLR 2019. Project page: http://shape2prog.csail.mit.edu 

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Representation Learning on Graphs with Jumping Knowledge Networks


Jun 25, 2018
Keyulu Xu, Chengtao Li, Yonglong Tian, Tomohiro Sonobe, Ken-ichi Kawarabayashi, Stefanie Jegelka

* ICML 2018, accepted as a long oral presentation 

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DeepID-Net: Deformable Deep Convolutional Neural Networks for Object Detection


Jun 02, 2015
Wanli Ouyang, Xiaogang Wang, Xingyu Zeng, Shi Qiu, Ping Luo, Yonglong Tian, Hongsheng Li, Shuo Yang, Zhe Wang, Chen-Change Loy, Xiaoou Tang

* CVPR15, arXiv admin note: substantial text overlap with arXiv:1409.3505 

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Pedestrian Detection aided by Deep Learning Semantic Tasks


Nov 29, 2014
Yonglong Tian, Ping Luo, Xiaogang Wang, Xiaoou Tang


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DeepID-Net: multi-stage and deformable deep convolutional neural networks for object detection


Sep 11, 2014
Wanli Ouyang, Ping Luo, Xingyu Zeng, Shi Qiu, Yonglong Tian, Hongsheng Li, Shuo Yang, Zhe Wang, Yuanjun Xiong, Chen Qian, Zhenyao Zhu, Ruohui Wang, Chen-Change Loy, Xiaogang Wang, Xiaoou Tang


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