Search "+Innovation -Paper -Paper/Graves2016DNC -Paper/Pugliese2017 -Diversity +Non-backtracking matrix +Beer -Neural doodle -Residual leanrning"

Positive matches

• 0.113 + - Network science
• 0.028 + - Trappist beer
• 0.028 + - Food
• 0.028 + - Andy Connelly
• 0.026 + - Diffusion of innovations
• 0.025 + - Cheese
• 0.023 + - Bread
• 0.023 + - Cinder toffee
• 0.017 + - Link prediction
• 0.011 + - Complex systems
• 0.011 + - Link analysis
• 0.010 + - Simplicial complex
• 0.009 + - Network datasets
• 0.007 + - Creative work
• 0.007 + - Meme
• 0.007 + - Andreas Wagner
• 0.007 + - Basic research
• 0.007 + - William Rosen
• 0.007 + - Dynamical system
• 0.007 + - Innovation hot spots

Negative matches

• 0.117 + - Residual Learning
• 0.111 + - National science production
• 0.067 + - Meta learning
• 0.065 + - Deep learning
• 0.061 + - Deep generative models
• 0.056 + - National scientific development
• 0.030 + - Learning
• 0.026 + - Differentiable neural computers
• 0.022 + - Neural Turing machine
• 0.022 + - Alex Graves
• 0.022 + - DeepMind
• 0.016 + - Amazon Elastic Compute Cloud
• 0.011 + - Dropout
• 0.010 + - Artificial neural network
• 0.009 + - Natural language processing
• 0.008 + - Reinforcement learning
• 0.006 + - Machine translation
• 0.006 + - Brain and deep learning
• 0.005 + - Keras
• 0.005 + - Generative adversarial network