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Positive matches

• 0.033 + - Interdisciplinary research
• 0.033 + - Network geometry
• 0.032 + - Data analysis
• 0.028 + - Natural language processing
• 0.027 + - Continuous embedding
• 0.018 + - word2vec
• 0.013 + - Pointwise mutual information
• 0.013 + - Policy
• 0.011 + - Paper/MacKay1991
• 0.009 + - tf-idf
• 0.008 + - PyTorch-BigGraph
• 0.008 + - Science policy
• 0.008 + - GraphSAGE
• 0.008 + - NLP
• 0.007 + - StanfordNLP
• 0.006 + - Peer review
• 0.006 + - Paper/Tshitoyan2019unsupervised
• 0.005 + - Scientific communication
• 0.005 + - Collaborative software
• 0.005 + - Edwin Thompson Jaynes

Negative matches

• 0.011 + - Residual leanrning
• 0.006 + - Paper/Gatys2015
• 0.006 + - Residual Learning
• 0.006 + - Deep learning
• 0.003 + - CNN
• 0.003 + - Deep generative models
• 0.002 + - Artificial neural network
• 0.002 + - Meta learning
• 0.001 + - Neural doodle
• 0.001 + - Long short-term memory
• 0.001 + - Archetype
• 0.000 + - Keras
• 0.000 + - Generative adversarial networks
• 0.000 + - Brain and deep learning
• 0.000 + - Theano
• 0.000 + - Dropout
• 0.000 + - Paper/Cooijmans2016
• 0.000 + - Paper/Hochreiter1997
• 0.000 + - KoNLPy