Search "+Home -Bookshelf +Funny things +Alan Moore +YY +Sociology -Donald Knuth +Probability Theory: The Logic of Science +Math +David MacKay +Science of science +Science +Scientometrics +Books +Industry-Academic Partnership +Sentence embedding +Scientific consensus +Map of science -G. Dobínski +Continuous embedding +Natural language processing +Biomedical natural language processing +GloVe +Peer review +Graph embedding +Interdisciplinary research +CNN +Information theory +Policy -word2vec"

Positive matches

• 0.044 + - Convolutional neural network
• 0.043 + - Word embedding
• 0.043 + - Migration
• 0.035 + - Network geometry
• 0.031 + - Lexical feature selection
• 0.025 + - Science policy
• 0.017 + - Public health policy
• 0.017 + - Probability theory
• 0.011 + - Paper/MacKay1991
• 0.010 + - Research advices
• 0.009 + - PyTorch-BigGraph
• 0.008 + - GraphSAGE
• 0.008 + - Scientific publication
• 0.007 + - NLP
• 0.007 + - StanfordNLP
• 0.007 + - Text analysis
• 0.007 + - Topic model
• 0.007 + - Embedded topic model
• 0.006 + - Residual Learning
• 0.006 + - Scientific communication

Negative matches

• 0.003 + - Softmax function
• 0.002 + - Ilya Sutskever
• 0.001 + - Chris McCormick
• 0.001 + - Paper/Perozzi2014
• 0.001 + - Paper/Hamilton2016
• 0.001 + - Neural network
• 0.001 + - Clinical concept embedding
• 0.001 + - Paper/Levy2014
• 0.001 + - Gender bias
• 0.001 + - Softmax
• 0.001 + - Gensim
• 0.001 + - Tomas Mikolov
• 0.001 + - Paper/Levy2014a
• 0.001 + - wiki2vec
• 0.001 + - Finkbeiner test
• 0.001 + - Skip-gram
• 0.001 + - sense2vec
• 0.000 + - Neuron
• 0.000 + - tfidf
• 0.000 + - Liquid state machine