Search "+Food -Beer -Cinder toffee -Deep learning +Autoencoder -MusicVAE +Odor -Jürgen Schmidhuber +Archetype"

Positive matches

• 0.110 + - Sentiment analysis
• 0.108 + - Olfaction
• 0.059 + - Social media
• 0.036 + - Generative adversarial network
• 0.017 + - Variational Autoencoder
• 0.016 + - Paper/Vincent2010
• 0.012 + - Unemployment
• 0.011 + - Wine pairing
• 0.009 + - Stretching
• 0.009 + - Music
• 0.008 + - Human mobility
• 0.006 + - Network science
• 0.006 + - Generative adversarial networks
• 0.004 + - Genetically modified organism
• 0.004 + - Food safety
• 0.004 + - Acceptable daily intake
• 0.004 + - Nutrient
• 0.004 + - Wine
• 0.004 + - Hamburger
• 0.004 + - Milk

Negative matches

• 0.082 + - Andy Connelly
• 0.057 + - Musical composition
• 0.041 + - Cheese
• 0.037 + - Variational autoencoder
• 0.031 + - Bread
• 0.028 + - Trappist beer
• 0.016 + - Residual leanrning
• 0.012 + - Restaurants
• 0.010 + - Cake
• 0.009 + - Catching Fire: How Cooking Made Us Human
• 0.009 + - Calorie
• 0.009 + - Reinforcement learning
• 0.007 + - Food pairing
• 0.006 + - Amazon EC2
• 0.006 + - Modeling animal behaviors with reinforcement learning
• 0.006 + - Cecilia Mascolo
• 0.006 + - TensorFlow
• 0.006 + - Marc'Aurelio Ranzato
• 0.006 + - Residual Learning
• 0.005 + - Attention