User contributions for Rqiao
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17 December 2015
- 23:2323:23, 17 December 2015 diff hist +4 learning Long-Range Vision for Autonomous Off-Road Driving →Feature Extraction
- 23:2223:22, 17 December 2015 diff hist +203 learning Long-Range Vision for Autonomous Off-Road Driving →Feature Extraction
- 23:1723:17, 17 December 2015 diff hist +1 learning Long-Range Vision for Autonomous Off-Road Driving →Related Work
- 23:1623:16, 17 December 2015 diff hist +833 learning Long-Range Vision for Autonomous Off-Road Driving →Related Work
- 22:1122:11, 17 December 2015 diff hist +43 deep Sparse Rectifier Neural Networks →Biological Plausibility and Sparsity
16 December 2015
- 22:5122:51, 16 December 2015 diff hist +380 deep Convolutional Neural Networks For LVCSR →Conclusions and Discussions
- 22:4022:40, 16 December 2015 diff hist −2 deep Convolutional Neural Networks For LVCSR →Conclusions and Discussions
- 22:2722:27, 16 December 2015 diff hist −2 very Deep Convoloutional Networks for Large-Scale Image Recognition →Training
- 22:2722:27, 16 December 2015 diff hist +367 very Deep Convoloutional Networks for Large-Scale Image Recognition →Training
1 December 2015
- 14:2114:21, 1 December 2015 diff hist −4 deep Learning of the tissue-regulated splicing code →Training the model
- 14:1914:19, 1 December 2015 diff hist +4 deep Learning of the tissue-regulated splicing code →Training the model
- 14:1914:19, 1 December 2015 diff hist +1 deep Learning of the tissue-regulated splicing code →Training the model
- 14:1814:18, 1 December 2015 diff hist +1,717 deep Learning of the tissue-regulated splicing code No edit summary
18 November 2015
- 22:3322:33, 18 November 2015 diff hist +1 dropout →Applying dropout to linear regression
- 22:3222:32, 18 November 2015 diff hist +389 dropout →Applying dropout to linear regression
- 22:2922:29, 18 November 2015 diff hist +207 dropout →Applying dropout to linear regression
- 22:2422:24, 18 November 2015 diff hist +815 dropout →Model
- 21:5821:58, 18 November 2015 diff hist +3 f15Stat946PaperSignUp →Set B
17 November 2015
- 11:3211:32, 17 November 2015 diff hist +1 learning Phrase Representations →References
- 11:3211:32, 17 November 2015 diff hist +29 learning Phrase Representations No edit summary
- 11:3111:31, 17 November 2015 diff hist +306 learning Phrase Representations →Scoring Phrase Pairs with RNN Encoder–Decoder
- 11:2911:29, 17 November 2015 diff hist +405 learning Phrase Representations →Scoring Phrase Pairs with RNN Encoder–Decoder
- 11:2511:25, 17 November 2015 diff hist +468 learning Phrase Representations No edit summary
16 November 2015
- 22:0622:06, 16 November 2015 diff hist +721 learning Phrase Representations →Experiments
- 21:5821:58, 16 November 2015 diff hist 0 N File:Encdec3.png No edit summary current
- 21:5821:58, 16 November 2015 diff hist +340 learning Phrase Representations No edit summary
- 21:4321:43, 16 November 2015 diff hist +875 learning Phrase Representations →Hidden Unit that Adaptively Remembers and Forgets
- 21:3721:37, 16 November 2015 diff hist +880 learning Phrase Representations →RNN Encoder–Decoder
- 21:1621:16, 16 November 2015 diff hist 0 N File:Encdec2.png No edit summary current
- 21:1521:15, 16 November 2015 diff hist +250 learning Phrase Representations →RNN Encoder–Decoder
- 20:3720:37, 16 November 2015 diff hist +618 learning Phrase Representations →RNN Encoder–Decoder
- 20:3220:32, 16 November 2015 diff hist +224 learning Phrase Representations →RNN Encoder–Decoder
- 20:2220:22, 16 November 2015 diff hist +416 learning Phrase Representations →RNN Encoder–Decoder
- 20:1620:16, 16 November 2015 diff hist +1,238 learning Phrase Representations →RNN Encoder–Decoder
- 19:4519:45, 16 November 2015 diff hist +124 learning Phrase Representations No edit summary
- 19:4419:44, 16 November 2015 diff hist 0 N File:Encdec1.png No edit summary current
- 19:4319:43, 16 November 2015 diff hist +742 N learning Phrase Representations Created page with "= Introduction = In this paper, Cho et al. propose a novel neural network model called RNN Encoder–Decoder that consists of two recurrent neural networks (RNN). One RNN encode..."
12 November 2015
- 21:4221:42, 12 November 2015 diff hist +64 neural Machine Translation: Jointly Learning to Align and Translate →Aligment
- 21:3821:38, 12 November 2015 diff hist +1 neural Machine Translation: Jointly Learning to Align and Translate →Decoding
- 21:3521:35, 12 November 2015 diff hist +58 neural Machine Translation: Jointly Learning to Align and Translate →Decoding
- 21:1821:18, 12 November 2015 diff hist +2 neural Machine Translation: Jointly Learning to Align and Translate →Reference
- 21:1721:17, 12 November 2015 diff hist +27 neural Machine Translation: Jointly Learning to Align and Translate No edit summary
- 21:1621:16, 12 November 2015 diff hist +452 neural Machine Translation: Jointly Learning to Align and Translate →Previous methods
- 12:2012:20, 12 November 2015 diff hist −1 graves et al., Speech recognition with deep recurrent neural networks →Further works
- 12:1912:19, 12 November 2015 diff hist +618 graves et al., Speech recognition with deep recurrent neural networks →Motivation
- 12:1612:16, 12 November 2015 diff hist +81 graves et al., Speech recognition with deep recurrent neural networks →Motivation
- 12:1412:14, 12 November 2015 diff hist −1,071 graves et al., Speech recognition with deep recurrent neural networks →References
7 November 2015
- 15:0015:00, 7 November 2015 diff hist +2 f15Stat946PaperSignUp →Set B
- 15:0015:00, 7 November 2015 diff hist +207 f15Stat946PaperSignUp No edit summary