Jeffrey Pennington

Publications by Year

Research Areas

Neural Networks and Applications, Gaussian Processes and Bayesian Inference, Stochastic Gradient Optimization Techniques, Machine Learning and Data Classification, Adversarial Robustness in Machine Learning

Most-Cited Works

• → Glove: Global Vectors for Word Representation(2014)33,361 cited
• Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions(2011)
• → Deep Neural Networks as Gaussian Processes(2017)335 cited
• → Statistical Mechanics of Deep Learning(2019)238 cited
• → Sensitivity and Generalization in Neural Networks: an Empirical Study(2018)224 cited
• → Dynamical Isometry and a Mean Field Theory of CNNs: How to Train\n 10,000-Layer Vanilla Convolutional Neural Networks(2018)175 cited
• → Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes(2018)169 cited
• → Leading singularities and off-shell conformal integrals(2013)133 cited
• Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice(2017)