Search "+KenLM -Brain and deep learning"

Positive matches

• 0.494 + - Natural language processing
• 0.088 + - NLP
• 0.077 + - Biomedical natural language processing
• 0.059 + - spaCy
• 0.052 + - CNN
• 0.031 + - StanfordNLP
• 0.028 + - scispaCy
• 0.026 + - Lexical feature selection
• 0.025 + - Convolutional neural network
• 0.010 + - Residual Learning
• 0.008 + - Recurrent neural network
• 0.007 + - Text analysis
• 0.007 + - RNN
• 0.006 + - Pointwise mutual information
• 0.006 + - Generative adversarial networks
• 0.005 + - Computational creativity
• 0.005 + - Residual leanrning
• 0.004 + - Gradient descent
• 0.002 + - Archetype
• 0.001 + - Sentiment analysis

Negative matches

• 0.250 + - Brain
• 0.246 + - Deep learning
• 0.056 + - Artificial neural network
• 0.051 + - Beer
• 0.043 + - Machine learning
• 0.028 + - Dropout
• 0.026 + - Language
• 0.021 + - Machine translation
• 0.020 + - Deep generative models
• 0.019 + - Meta learning
• 0.019 + - Neural doodle
• 0.018 + - Differentiable neural computers
• 0.012 + - Modular structure of brain
• 0.012 + - Allen Institute for Brain Science
• 0.011 + - Paper/Gatys2015
• 0.011 + - Efficiency of brain
• 0.011 + - Brain structural variation
• 0.010 + - Thermostat
• 0.010 + - Generative adversarial network
• 0.010 + - Keras