Search "+Diversity -Paper +Paper/Gopalan2012community +Paper/Hamilton2016 +Paper/Heaberlin2015 -Paper/Goodfellow2014 +Paper/McNerney2018production -Generative adversarial network +Beer"

Positive matches

• 0.111 + - Innovation
• 0.111 + - Norm
• 0.100 + - Wassily Leontief
• 0.056 + - Norm (social)
• 0.054 + - Community detectability
• 0.028 + - Trappist beer
• 0.028 + - Andy Connelly
• 0.028 + - Stochastic block model
• 0.028 + - David Blei
• 0.028 + - Prem Gopalan
• 0.027 + - Food
• 0.025 + - Word embedding
• 0.024 + - Cheese
• 0.023 + - Cinder toffee
• 0.021 + - Bread
• 0.020 + - word2vec
• 0.019 + - Dan Jurafsky
• 0.019 + - Jure Leskovec
• 0.019 + - William L. Hamilton
• 0.019 + - Orthogonal Procrustes problem

Negative matches

• 0.083 + - Generative adversarial networks
• 0.029 + - Ian J. Goodfellow
• 0.028 + - Yoshua Bengio
• 0.028 + - Deep learning
• 0.014 + - Meta learning
• 0.014 + - Machine translation
• 0.011 + - Artificial neural network
• 0.007 + - Learning
• 0.006 + - Amazon Elastic Compute Cloud
• 0.005 + - Dropout
• 0.005 + - Differentiable neural computers
• 0.004 + - Residual leanrning
• 0.004 + - Reinforcement learning
• 0.003 + - Theano
• 0.003 + - Paper/Vincent2010
• 0.003 + - Autoencoder
• 0.003 + - Natural language processing
• 0.003 + - Image completion
• 0.003 + - Attention (Deep learning)
• 0.002 + - Residual Learning