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Positive matches

• 0.031 + - Interdisciplinary research
• 0.026 + - Science policy
• 0.024 + - Probability
• 0.017 + - Public health policy
• 0.014 + - Continuous embedding
• 0.012 + - Sentence embedding
• 0.011 + - Software engineering
• 0.011 + - Communication
• 0.011 + - Information theory
• 0.011 + - Software license
• 0.011 + - Sure Thing hypothesis
• 0.009 + - PyTorch-BigGraph
• 0.008 + - Revision control
• 0.008 + - Hessian matrix
• 0.008 + - Natural language processing
• 0.007 + - Reproducible research
• 0.007 + - Research tools
• 0.005 + - Paper/Tshitoyan2019unsupervised
• 0.005 + - Collaborative software
• 0.005 + - Stochastic process

Negative matches

• 0.004 + - Softmax function
• 0.002 + - Softmax
• 0.002 + - Liquid state machine
• 0.002 + - WordRank
• 0.002 + - Sentiment analysis
• 0.001 + - tf-idf
• 0.001 + - Finkbeiner test
• 0.001 + - Neural network
• 0.001 + - Skip-gram
• 0.001 + - Deep learning
• 0.001 + - TensorFlow
• 0.001 + - Chris McCormick
• 0.001 + - Gender bias
• 0.001 + - sense2vec
• 0.001 + - Clinical concept embedding
• 0.001 + - Ilya Sutskever
• 0.001 + - wiki2vec
• 0.001 + - Paper/Hamilton2016
• 0.001 + - Paper/Levy2014
• 0.001 + - Tomas Mikolov