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cs.LG2020
How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks
Keyulu Xu, Mozhi Zhang, Jingling Li +3
We study how neural networks trained by gradient descent extrapolate, i.e., what they learn outside the support of the training distribution. Previous works report mixed empirical…
cs.LG2020
Understanding Generalization in Deep Learning via Tensor Methods
Jingling Li, Yanchao Sun, Jiahao Su +2
Deep neural networks generalize well on unseen data though the number of parameters often far exceeds the number of training examples. Recently proposed complexity measures have pr…
cs.LG2019
What Can Neural Networks Reason About?
Keyulu Xu, Jingling Li, Mozhi Zhang +3
Neural networks have succeeded in many reasoning tasks. Empirically, these tasks require specialized network structures, e.g., Graph Neural Networks (GNNs) perform well on many suc…