Keyulu Xu

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MIT

Noisy Labels Can Induce Good Representations

The current success of deep learning depends on large-scale labeled data...
12/23/2020 ∙ by Jingling Li, et al. ∙ 11 ∙ share

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Graph Adversarial Networks: Protecting Information against Adversarial Attacks

We study the problem of protecting information when learning with graph ...
09/28/2020 ∙ by Peiyuan Liao, et al. ∙ 20 ∙ share

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How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks

We study how neural networks trained by gradient descent extrapolate, i....
09/24/2020 ∙ by Keyulu Xu, et al. ∙ 68 ∙ share

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GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training

Normalization plays an important role in the optimization of deep neural...
09/07/2020 ∙ by Tianle Cai, et al. ∙ 0 ∙ share

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Are Girls Neko or Shōjo? Cross-Lingual Alignment of Non-Isomorphic Embeddings with Iterative Normalization

Cross-lingual word embeddings (CLWE) underlie many multilingual natural ...
06/04/2019 ∙ by Mozhi Zhang, et al. ∙ 0 ∙ share

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What Can Neural Networks Reason About?

Neural networks have successfully been applied to solving reasoning task...
05/30/2019 ∙ by Keyulu Xu, et al. ∙ 0 ∙ share

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Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels

While graph kernels (GKs) are easy to train and enjoy provable theoretic...
05/30/2019 ∙ by Simon S. Du, et al. ∙ 4 ∙ share

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How Powerful are Graph Neural Networks?

Graph Neural Networks (GNNs) for representation learning of graphs broad...
10/01/2018 ∙ by Keyulu Xu, et al. ∙ 13 ∙ share

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Representation Learning on Graphs with Jumping Knowledge Networks

Recent deep learning approaches for representation learning on graphs fo...
06/09/2018 ∙ by Keyulu Xu, et al. ∙ 0 ∙ share

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Keyulu Xu

Featured Co-authors

Ruslan Salakhutdinov

Tie-Yan Liu

Barnabas Poczos

Jure Leskovec

Liwei Wang

Simon S. Du

Stefanie Jegelka

Tommi Jaakkola

Di He

Jimmy Ba

Jordan Boyd-Graber

Noisy Labels Can Induce Good Representations

Graph Adversarial Networks: Protecting Information against Adversarial Attacks

How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks

GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training

Are Girls Neko or Shōjo? Cross-Lingual Alignment of Non-Isomorphic Embeddings with Iterative Normalization

What Can Neural Networks Reason About?

Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels

How Powerful are Graph Neural Networks?

Representation Learning on Graphs with Jumping Knowledge Networks