Weidi Xu

Artificial Intelligence · 2016–2020

A researcher in the Science corpus: 3 papers; trusts 48 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 54 citations into it; #31,709 of 35,345 by trust here, #14,718 by citations
• Natural Language Processing — 33 citations into it
• Computer Vision and Pattern Recognition — 31 citations into it; #19,519 of 21,575 by trust here, #11,950 by citations
• Generative Models — 17 citations into it
• Optimization & Training — 12 citations into it
• Representation & Self-Supervised Learning — 12 citations into it
• Model Architectures — 10 citations into it
• Probabilistic & Bayesian Methods — 8 citations into it

Whom Weidi Xu trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Diederik P. Kingma
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. Danilo Jimenez Rezende
5. Sergey Ioffe
6. Ronald J. Williams
7. Max Welling
8. Alex Krizhevsky
9. Sepp Hochreiter
10. Jimmy Ba

Who trusts Weidi Xu overall

1. Iqbal H. Sarker
2. Babak Esmaeili
3. Jason Ramapuram
4. Hui Liu
5. Yu Meng
6. Xinting Huang
7. Dinghan Shen
8. Jiaao Chen
9. Ziqi Wang
10. Hao Wu

Papers from Weidi Xu's perspective

Ordered by how strongly the researchers Weidi Xu trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Learning Multiple Layers of Features from Tiny Images
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Variational Autoencoder for Semi-Supervised Text Classification (2017) — 236 citations
• Question Directed Graph Attention Network for Numerical Reasoning over Text (2020) — 69 citations
• Semi-supervised Variational Autoencoders for Sequence Classification (2016) — 7 citations