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 +Graph embedding +PyTorch-BigGraph +Probability theory +Paper/MacKay1991 +Interdisciplinary research +G. Dobínski -Hessian matrix +Bayesian inference +Migration -Stochastic process +Continuous embedding +Topic model +Science policy +GraphSAGE +LDA -word2vec"

Positive matches

• 0.109 + - Network geometry
• 0.038 + - Probability
• 0.023 + - Topic modeling
• 0.023 + - Policy
• 0.019 + - Embedded topic model
• 0.018 + - Industry-Academic Partnership
• 0.017 + - PyTorch
• 0.016 + - Topic mapping
• 0.013 + - Edwin Thompson Jaynes
• 0.013 + - Research funding
• 0.012 + - Latent Dirichlet allocation
• 0.011 + - Information theory
• 0.010 + - Natural language processing
• 0.008 + - Paper
• 0.007 + - Word embedding
• 0.007 + - Scientific communication
• 0.007 + - Sentence embedding
• 0.006 + - Twitter
• 0.005 + - Bibliometrics
• 0.005 + - GloVe

Negative matches

• 0.003 + - Softmax function
• 0.002 + - tf-idf
• 0.002 + - Recurrent neural network
• 0.002 + - Paper/Hamilton2016
• 0.002 + - Paper/Perozzi2014
• 0.002 + - Ilya Sutskever
• 0.002 + - Sentiment analysis
• 0.001 + - Chris McCormick
• 0.001 + - Clinical concept embedding
• 0.001 + - sense2vec
• 0.001 + - Archetype
• 0.001 + - Neural network
• 0.001 + - TensorFlow
• 0.001 + - Paper/Levy2014a
• 0.001 + - Gensim
• 0.001 + - Skip-gram
• 0.001 + - Deep learning
• 0.001 + - Gender bias
• 0.001 + - Softmax
• 0.001 + - Finkbeiner test