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Positive matches

• 0.029 + - Lexical feature selection
• 0.029 + - Interdisciplinary research
• 0.026 + - Science policy
• 0.025 + - Industry-Academic Partnership
• 0.023 + - Word embedding
• 0.017 + - Opioid crisis
• 0.017 + - Probability theory
• 0.014 + - Network geometry
• 0.011 + - Continuous embedding
• 0.011 + - Communication
• 0.010 + - CNN
• 0.009 + - Edwin Thompson Jaynes
• 0.009 + - Paper
• 0.008 + - PyTorch-BigGraph
• 0.008 + - GraphSAGE
• 0.007 + - Jeannette M. Wing
• 0.006 + - Pointwise mutual information
• 0.006 + - Aaron Clauset
• 0.006 + - Scientific publication
• 0.006 + - NLP

Negative matches

• 0.009 + - Deep learning
• 0.009 + - Residual leanrning
• 0.006 + - Convolutional neural network
• 0.003 + - Beer
• 0.002 + - Artificial neural network
• 0.002 + - Meta learning
• 0.001 + - Dropout
• 0.001 + - Jürgen Schmidhuber
• 0.001 + - Marc'Aurelio Ranzato
• 0.001 + - Andrew Ng
• 0.001 + - Yann LeCun
• 0.001 + - Brain and deep learning
• 0.001 + - Autoencoder
• 0.001 + - Generative adversarial networks
• 0.001 + - Generative adversarial network
• 0.001 + - Yoshua Bengio
• 0.001 + - Keras
• 0.001 + - Language
• 0.001 + - Machine translation
• 0.001 + - Deep learning and graphs