representation learning

不安全 2024-06-02 阅读缓存

Leveraging Natural Supervision for Language Representation Learning and Generation: Acknowledgements

收藏阅读缓存
不安全 2024-06-02 阅读缓存

Leveraging Natural Supervision for Language Representation Learning and Generation: Abstract

收藏阅读缓存
OpenAI 2022-06-23 games · representation learning · reinforcement learning · community 阅读缓存

Learning to play Minecraft with Video PreTraining

收藏阅读缓存
谷歌研发博客 2021-05-12 computer vision · deep learning · machine perception · multimodal learning 阅读缓存

ALIGN: Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision

收藏阅读缓存
谷歌研发博客 2019-06-26 graph mining · machine learning · ml · social networks 阅读缓存

Innovations in Graph Representation Learning

收藏阅读缓存
爱可可 - 爱生活 2017-03-11 阅读缓存

《Notes on Representation Learning Continued》 http://t.cn/RiQj1aN http://t.cn/RiQj1aCRT @爱可可-爱生活:【表示学习笔记】《Notes on Representation Learning | Open Data Science》by Zac Kriegman http://t.cn/RiQjuhw

收藏阅读缓存
爱可可 - 爱生活 2017-03-11 阅读缓存

【表示学习笔记】《Notes on Representation Learning | Open Data Science》by Zac Kriegman http://t.cn/RiQjuhw

收藏阅读缓存
爱可可 - 爱生活 2017-03-06 阅读缓存

《Online Multiview Representation Learning: Dropping Convexity for Better Efficiency》Z Chen, F L. Yang, C J. Li, T Zhao [Georgia Tech & Johns Hopkins University & Princeton University] (2017) http://t.cn/RiKFNNh

收藏阅读缓存
爱可可 - 爱生活 2017-02-23 阅读缓存

《InfoGAN学习笔记》by @黄锦池-hjimce http://t.cn/RJES7zORT @爱可可-爱生活:《InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets》X Chen, Y Duan, R Houthooft, J Schulman, I Sutskever, P Abbeel [UC Berkeley & OpenAI] (2016) http://t.cn/R5X5gJq

收藏阅读缓存
爱可可 - 爱生活 2017-02-16 阅读缓存

【多粒度语言单元表示学习】《Representation Learning for Language Units of Different Granularity - YouTube》by Wenpeng Yin http://t.cn/RJlk5uY

收藏阅读缓存
爱可可 - 爱生活 2017-02-03 阅读缓存

Notes by Goku Mohandas http://t.cn/Rxd9vsXRT @爱可可-爱生活:《GRAM: Graph-based Attention Model for Healthcare Representation Learning》E Choi, M T Bahadori, L Song, W F. Stewart, J Sun [Georgia Institute of Technology & Sutter Health] (2016) http://t.cn/RxdKsaZ Home:http://t.cn/RxdKsaz GitHub:http://t.cn/RxdKsa7

收藏阅读缓存
爱可可 - 爱生活 2017-02-03 阅读缓存

《GRAM: Graph-based Attention Model for Healthcare Representation Learning》E Choi, M T Bahadori, L Song, W F. Stewart, J Sun [Georgia Institute of Technology & Sutter Health] (2016) http://t.cn/RxdKsaZ Home:http://t.cn/RxdKsaz GitHub:http://t.cn/RxdKsa7

收藏阅读缓存
爱可可 - 爱生活 2017-01-23 阅读缓存

《Linear Disentangled Representation Learning for Facial Actions》X Xiang, T D. Tran [Johns Hopkins University] (2017) http://t.cn/Rxw3iMy

收藏阅读缓存
爱可可 - 爱生活 2017-01-10 阅读缓存

Keras implementation by Thibault de Boissiere GitHub:http://t.cn/RMxTrQSRT @爱可可-爱生活:《InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets》X Chen, Y Duan, R Houthooft, J Schulman, I Sutskever, P Abbeel [UC Berkeley & OpenAI] (2016) http://t.cn/R5X5gJq

收藏阅读缓存
爱可可 - 爱生活 2017-01-10 阅读缓存

《NIPS 2016 Workshop on Representation Learning in Artificial and Biological Neural Networks (MLINI 2016)》L Wehbe, A Nunez-Elizalde, M v Gerven, I Rish, B Murphy, M Grosse-Wentrup, G Langs, G Cecchi (2017) http://t.cn/RMxW4mr

收藏阅读缓存
爱可可 - 爱生活 2017-01-09 阅读缓存

《Autoencoder Regularized Network For Driving Style Representation Learning》W Dong, T Yuan, K Yang, C Li, S Zhang [IBM Research – China] (2017) http://t.cn/RMf3rvc

收藏阅读缓存
爱可可 - 爱生活 2017-01-05 阅读缓存

【第二届NLP表示学习Workshop】“2nd Workshop on Representation Learning for NLP” http://t.cn/RMLo6Vw

收藏阅读缓存
爱可可 - 爱生活 2017-01-02 阅读缓存

《Image-Text Multi-Modal Representation Learning by Adversarial Backpropagation》G Park, W Im [Korea Advanced Institute of Science and Technology (KAIST)] (2016) http://t.cn/RMvf6cD

收藏阅读缓存
爱可可 - 爱生活 2016-12-25 阅读缓存

《A Survey of Inductive Biases for Factorial Representation-Learning》K Ridgeway (2016) http://t.cn/RIlGFLu

收藏阅读缓存
爱可可 - 爱生活 2016-11-25 阅读缓存

《iCaRL: Incremental Classifier and Representation Learning》S Rebuffi, A Kolesnikov, C H. Lampert [University of Oxford & IST Austria] (2016) http://t.cn/RfCn6bD

收藏阅读缓存
爱可可 - 爱生活 2016-11-13 阅读缓存

《对抗的深度卷积生成网络来学习无监督表示》via:巧克力爱松露 http://t.cn/RVv6MNWRT @爱可可-爱生活:【论文:基于深度卷积生成式对抗网络的无监督表示学习】《Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks》A Radford, L Metz[indico Research], S Chintala[Facebook AI Research] (2015) http://t.cn/RU1Xt1t

收藏阅读缓存
爱可可 - 爱生活 2016-10-25 阅读缓存

'(Keras)Autoencoder network for learning a continuous representation of molecular structures.' by Max Hodak GitHub: http://t.cn/RVjhCMI http://t.cn/RVj6gm2RT @爱可可-爱生活:《Automatic chemical design using a data-driven continuous representation of molecules》R Gómez-Bombarelli, D Duvenaud, J M Hernández-Lobato… [Harvard University & University of Toronto] (2016) http://t.cn/RVqinux

收藏阅读缓存
爱可可 - 爱生活 2016-10-19 阅读缓存

'A tensorflow implementation of informative generative adversarial network (InfoGAN ).' by Namju Kim GitHub: http://t.cn/RVo2UfD //@爱可可-爱生活: InfoGAN GitHub: http://t.cn/R5odT4jRT @爱可可-爱生活:《InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets》X Chen, Y Duan, R Houthooft, J Schulman, I Sutskever, P Abbeel [UC Berkeley & OpenAI] (2016) http://t.cn/R5X5gJq

收藏阅读缓存
爱可可 - 爱生活 2016-10-13 阅读缓存

《From phonemes to images: levels of representation in a recurrent neural model of visually-grounded language learning》L Gelderloos, G Chrupała [Tilburg University] (2016) http://t.cn/RVt591k

收藏阅读缓存
爱可可 - 爱生活 2016-09-05 阅读缓存

《Learning a Predictable and Generative Vector Representation for Objects》R Girdhar, D F. Fouhey, M Rodriguez, A Gupta [CMU] (ECCV 2016) http://t.cn/RcyvLiS GitHub:http://t.cn/Rc2wOav models:http://t.cn/RcyvLio

收藏阅读缓存
爱可可 - 爱生活 2016-09-04 阅读缓存

爱可可老师24小时热门分享：1、《卷积神经网络工作原理直观的解释？ - 知乎》2、《Scikit-learn技巧（拓展）总结》3、《Learning Deep Representation for Imbalanced Classification》4、《Elementary Algorithms》5、《2016滴滴大数据算法大赛参赛总结》…… http://t.cn/RcLY9fI

收藏阅读缓存
爱可可 - 爱生活 2016-09-04 阅读缓存

//@我爱机器学习: 汤晓鸥老师团队的工作，从Triplet Embedding进化到Quintuplet Embedding，前者只强调不平衡类别间的区别，后者同时还考虑少数类内部不同cluster之间的区别，数量也由三元组变到五元组。RT @爱可可-爱生活:《Learning Deep Representation for Imbalanced Classification》C Huang, Y Li, C Change Loy, X Tang [The Chinese University of Hong Kong] (CVPR 2016) http://t.cn/Rc2nKFb Home(w/Slides&Poster&Code):http://t.cn/Rc2nKFG

收藏阅读缓存
爱可可 - 爱生活 2016-09-04 阅读缓存

《Learning Deep Representation for Imbalanced Classification》C Huang, Y Li, C Change Loy, X Tang [The Chinese University of Hong Kong] (CVPR 2016) http://t.cn/Rc2nKFb Home(w/Slides&Poster&Code):http://t.cn/Rc2nKFG

收藏阅读缓存
爱可可 - 爱生活 2016-09-04 阅读缓存

“Proceedings of the 1st Workshop on Representation Learning for NLP” http://t.cn/Rc28BYj

收藏阅读缓存