Search "+Food -Beer -Yoshua Bengio +Fig +Paper/Bahdanau2015 -RNN -Prediction using social media -SAX -Autoencoder"

Positive matches

• 0.036 + - Attention
• 0.022 + - Dzmitry Bahdanau
• 0.021 + - Kyunghyun Cho
• 0.019 + - Odor
• 0.019 + - Paper
• 0.014 + - Wine pairing
• 0.011 + - Stretching
• 0.009 + - Music
• 0.005 + - Computational creativity
• 0.005 + - Musical composition
• 0.004 + - Social media
• 0.004 + - Attention (Deep learning)
• 0.003 + - Food pairing
• 0.003 + - Dim sum
• 0.003 + - Tofu
• 0.003 + - Restaurants
• 0.003 + - Dumpling
• 0.003 + - Public datasets
• 0.003 + - Rice
• 0.003 + - Catching Fire: How Cooking Made Us Human

Negative matches

• 0.133 + - Time series
• 0.088 + - Recurrent neural network
• 0.074 + - Deep learning
• 0.068 + - Correlation
• 0.050 + - Generative adversarial network
• 0.046 + - Paper/Vincent2010
• 0.035 + - Generative adversarial networks
• 0.035 + - Yogi Berra
• 0.033 + - Prediction
• 0.028 + - Trappist beer
• 0.028 + - Paper/Goodfellow2014
• 0.026 + - Andy Connelly
• 0.026 + - Cheese
• 0.023 + - Bread
• 0.023 + - Collective intelligence
• 0.023 + - Stock market prediction
• 0.020 + - Variational Autoencoder
• 0.020 + - MusicVAE
• 0.020 + - Variational autoencoder
• 0.017 + - Cinder toffee