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Positive matches

• 0.061 + - Graph embedding
• 0.030 + - Lexical feature selection
• 0.029 + - Word embedding
• 0.021 + - Interdisciplinary research
• 0.017 + - Lasswell's maxim
• 0.017 + - Probability theory
• 0.016 + - Industry-Academic Partnership
• 0.015 + - Software engineering in research
• 0.014 + - Software license
• 0.012 + - Policy
• 0.011 + - Software documentation
• 0.009 + - Text analysis
• 0.009 + - Science policy
• 0.009 + - Edwin Thompson Jaynes
• 0.009 + - Paper
• 0.008 + - Hessian matrix
• 0.008 + - GloVe
• 0.008 + - CNN
• 0.007 + - Embedded topic model
• 0.007 + - Pointwise mutual information

Negative matches

• 0.009 + - Residual leanrning
• 0.007 + - Convolutional neural network
• 0.007 + - Deep learning
• 0.002 + - Beer
• 0.001 + - Generative adversarial networks
• 0.001 + - Amazon Elastic Compute Cloud
• 0.001 + - Language
• 0.001 + - Deep learning and graphs
• 0.001 + - Jürgen Schmidhuber
• 0.001 + - Generative adversarial network
• 0.001 + - Marc'Aurelio Ranzato
• 0.001 + - Autoencoder
• 0.001 + - Learning
• 0.001 + - Meta learning
• 0.001 + - Machine translation
• 0.001 + - Quoc Le
• 0.000 + - Dropout
• 0.000 + - Keras
• 0.000 + - Deep generative models
• 0.000 + - Geoffrey Hinton