Kilian Weinberger

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Gao Huang （黄高）Associate Professor, Tsinghua UniversityVerified email at tsinghua.edu.cn
Laurens van der MaatenDistinguished Research Scientist, Meta AIVerified email at meta.com
Zhuang LiuResearch Scientist, Meta AI ResearchVerified email at berkeley.edu
Felix WuCharacter AIVerified email at character.ai
Geoff PleissAssistant Professor, University of British ColumbiaVerified email at stat.ubc.ca
Lawrence K SaulSenior Research Scientist, Center for Computational Mathematics, Flatiron InstituteVerified email at flatironinstitute.org
Chuan GuoResearch Scientist, FAIR, MetaVerified email at fb.com
Jacob GardnerUniversity of PennsylvaniaVerified email at seas.upenn.edu
Mark CampbellJohn A. Mellowes ‘60 Professor, Cornell UniversityVerified email at cornell.edu
Matt J. KusnerUniversity College LondonVerified email at ucl.ac.uk
Wei-Lun (Harry) Chao 趙偉崙Assistant Professor, The Ohio State UniversityVerified email at osu.edu
Yu SunPostdoc, Stanford UniversityVerified email at cs.stanford.edu
Zhixiang (Eddie) XuWashington UniversityVerified email at cse.wustl.edu
Minmin ChenResearch scientist, GoogleVerified email at google.com
bharath hariharanCornell UniversityVerified email at cs.cornell.edu
Stephen TyreeNVIDIAVerified email at nvidia.com
Fei ShaGoogle ResearchVerified email at feisha.org
Yan WangResearch Scientist, NVIDIA; ex-Waymo; PhD CornellVerified email at waymo.com
Yurong YouCornell UniversityVerified email at cornell.edu
Tianyi ZhangStanford UniversityVerified email at cornell.edu

Kilian Weinberger

Cornell University

Verified email at cornell.edu - Homepage

machine learning deep learning metric learning computer vision


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Densely connected convolutional networks G Huang, Z Liu, L Van Der Maaten, KQ Weinberger Proceedings of the IEEE conference on computer vision and pattern …, 2017	40377	2017
On calibration of modern neural networks C Guo, G Pleiss, Y Sun, KQ Weinberger International conference on machine learning, 1321-1330, 2017	4699	2017
Distance metric learning for large margin nearest neighbor classification. KQ Weinberger, LK Saul Journal of machine learning research 10 (2), 2009	4686	2009
Bertscore: Evaluating text generation with bert T Zhang, V Kishore, F Wu, KQ Weinberger, Y Artzi arXiv preprint arXiv:1904.09675, 2019	2851	2019
From word embeddings to document distances M Kusner, Y Sun, N Kolkin, K Weinberger International conference on machine learning, 957-966, 2015	2568	2015
Simplifying graph convolutional networks F Wu, A Souza, T Zhang, C Fifty, T Yu, K Weinberger International conference on machine learning, 6861-6871, 2019	2558	2019
Distance metric learning for large margin nearest neighbor classification KQ Weinberger, J Blitzer, L Saul Advances in neural information processing systems 18, 2005	2447	2005
Deep networks with stochastic depth G Huang, Y Sun, Z Liu, D Sedra, KQ Weinberger Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016	2398	2016
Advances in neural information processing systems A Krizhevsky (No Title), 1097, 2012	1719	2012
Compressing neural networks with the hashing trick W Chen, J Wilson, S Tyree, K Weinberger, Y Chen International conference on machine learning, 2285-2294, 2015	1358	2015
Unsupervised learning of image manifolds by semidefinite programming KQ Weinberger, LK Saul International journal of computer vision 70 (1), 77-90, 2006	1209	2006
Unsupervised learning of image manifolds by semidefinite programming KQ Weinberger, LK Saul CVPR 2, 988-995, 2004	1209	2004
Feature hashing for large scale multitask learning K Weinberger, A Dasgupta, J Langford, A Smola, J Attenberg Proceedings of the 26th annual international conference on machine learning …, 2009	1146	2009
Marginalized denoising autoencoders for domain adaptation M Chen, Z Xu, K Weinberger, F Sha arXiv preprint arXiv:1206.4683, 2012	976	2012
Pseudo-lidar from visual depth estimation: Bridging the gap in 3d object detection for autonomous driving Y Wang, WL Chao, D Garg, B Hariharan, M Campbell, KQ Weinberger Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019	968	2019
Gpytorch: Blackbox matrix-matrix gaussian process inference with gpu acceleration J Gardner, G Pleiss, KQ Weinberger, D Bindel, AG Wilson Advances in neural information processing systems 31, 2018	940	2018
Snapshot ensembles: Train 1, get m for free G Huang, Y Li, G Pleiss, Z Liu, JE Hopcroft, KQ Weinberger arXiv preprint arXiv:1704.00109, 2017	939	2017
Condensenet: An efficient densenet using learned group convolutions G Huang, S Liu, L Van der Maaten, KQ Weinberger Proceedings of the IEEE conference on computer vision and pattern …, 2018	883	2018
On fairness and calibration G Pleiss, M Raghavan, F Wu, J Kleinberg, KQ Weinberger Advances in neural information processing systems 30, 2017	843	2017
Multi-scale dense networks for resource efficient image classification G Huang, D Chen, T Li, F Wu, L Van Der Maaten, KQ Weinberger arXiv preprint arXiv:1703.09844, 2017	679	2017

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