User contributions for R6gong
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30 November 2020
- 17:1717:17, 30 November 2020 diff hist +2 m Surround Vehicle Motion Prediction →Input and output features
- 17:1517:15, 30 November 2020 diff hist +327 m Evaluating Machine Accuracy on ImageNet →Critiques
- 17:0617:06, 30 November 2020 diff hist +457 m Speech2Face: Learning the Face Behind a Voice →Discussion and Critiques
- 16:5216:52, 30 November 2020 diff hist +332 m Research Papers Classification System →Critique
- 16:4016:40, 30 November 2020 diff hist +195 m Mask RCNN →Critiques
- 16:0116:01, 30 November 2020 diff hist +331 m Describtion of Text Mining →Critiques
- 15:5515:55, 30 November 2020 diff hist −4 m Improving neural networks by preventing co-adaption of feature detectors →Reuters Corpus Volume
- 15:5315:53, 30 November 2020 diff hist +160 m Deep Learning for Cardiologist-level Myocardial Infarction Detection in Electrocardiograms →Critiques
- 15:4615:46, 30 November 2020 diff hist +221 m Loss Function Search for Face Recognition →Critiques
- 15:4215:42, 30 November 2020 diff hist +3 m Being Bayesian about Categorical Probability →Related Work
- 15:4015:40, 30 November 2020 diff hist +132 m Efficient kNN Classification with Different Numbers of Nearest Neighbors →Critiques
- 15:3215:32, 30 November 2020 diff hist +1 m Efficient kNN Classification with Different Numbers of Nearest Neighbors →Motivation
- 15:3015:30, 30 November 2020 diff hist 0 m Efficient kNN Classification with Different Numbers of Nearest Neighbors →Introduction
- 15:2815:28, 30 November 2020 diff hist 0 m A universal SNP and small-indel variant caller using deep neural networks →Critique
- 15:2815:28, 30 November 2020 diff hist +261 m A universal SNP and small-indel variant caller using deep neural networks →Critique
- 15:1815:18, 30 November 2020 diff hist +206 m Music Recommender System Based using CRNN →Critiques/ Insights:
- 15:0915:09, 30 November 2020 diff hist +1 m Music Recommender System Based using CRNN →Introduction and Objective:
23 November 2020
- 14:5614:56, 23 November 2020 diff hist +68 stat441F21 →Paper presentation
22 November 2020
- 23:0023:00, 22 November 2020 diff hist +672 Semantic Relation Classification——via Convolution Neural Network →References
- 22:5022:50, 22 November 2020 diff hist +2 Semantic Relation Classification——via Convolution Neural Network No edit summary
- 17:1117:11, 22 November 2020 diff hist −2 Semantic Relation Classification——via Convolution Neural Network →Introduction
- 17:1117:11, 22 November 2020 diff hist −161 Semantic Relation Classification——via Convolution Neural Network →Introduction
- 17:1017:10, 22 November 2020 diff hist +164 Semantic Relation Classification——via Convolution Neural Network →Introduction
- 17:0717:07, 22 November 2020 diff hist −161 Semantic Relation Classification——via Convolution Neural Network →Introduction
- 17:0717:07, 22 November 2020 diff hist +164 Semantic Relation Classification——via Convolution Neural Network →Introduction
- 17:0217:02, 22 November 2020 diff hist −6 Semantic Relation Classification——via Convolution Neural Network →Introduction
- 16:0616:06, 22 November 2020 diff hist +60 Semantic Relation Classification——via Convolution Neural Network No edit summary
- 16:0316:03, 22 November 2020 diff hist +74 Semantic Relation Classification——via Convolution Neural Network No edit summary
- 16:0216:02, 22 November 2020 diff hist −2 Semantic Relation Classification——via Convolution Neural Network No edit summary
- 16:0016:00, 22 November 2020 diff hist +226 Semantic Relation Classification——via Convolution Neural Network No edit summary
- 15:5515:55, 22 November 2020 diff hist −78 Semantic Relation Classification——via Convolution Neural Network No edit summary
- 15:5515:55, 22 November 2020 diff hist +78 Semantic Relation Classification——via Convolution Neural Network No edit summary
- 15:5115:51, 22 November 2020 diff hist +1,999 N Semantic Relation Classification——via Convolution Neural Network Created page with " After featurizing all words in the sentence. The sentence of length N can be expressed as a vector of length $N$, which looks like $$e=[e_{1},e_{2},\ldots,e_{N}]$$ and eac..."
- 15:4815:48, 22 November 2020 diff hist +134 stat441F21 →Paper presentation
11 November 2020
- 22:2922:29, 11 November 2020 diff hist −106 F21-STAT 441/841 CM 763-Proposal No edit summary
28 October 2020
- 14:5114:51, 28 October 2020 diff hist +147 F21-STAT 441/841 CM 763-Proposal No edit summary
9 October 2020
- 23:1823:18, 9 October 2020 diff hist −12 F21-STAT 441/841 CM 763-Proposal No edit summary
- 23:1723:17, 9 October 2020 diff hist +568 F21-STAT 441/841 CM 763-Proposal No edit summary
- 21:4521:45, 9 October 2020 diff hist +116 stat441F21 →Paper presentation