Scaling the Poisson GLM to massive neural datasets through polynomial approximations

Mathematics

• Polynomial Approximation 100%
• Generalized Linear Model 100%
• Approximates 50%
• Regularization 16%
• Maximum Likelihood 16%
• Nonlinear Term 16%
• Inference Method 16%
• Gaussian Distribution 16%
• Spike Train 16%
• Posterior Distribution 16%
• Closed Form Solution 16%
• Statistical Method 16%
• Sufficient Statistic 16%
• Marginal Likelihood 16%
• Log Likelihood 16%
• Quadratic Approximation 16%
• Spike Count 16%
• Statistical Dependency 16%

Neuroscience

• Generalized Linear Model 100%

Keyphrases

• Model Setting 20%