Wei Chen

Artificial Intelligence · with Banás · 2019–2022

A researcher in the Science corpus: 2 papers; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 25 citations into it
• Computer Vision and Pattern Recognition — 20 citations into it
• Generative Models — 15 citations into it
• Probabilistic & Bayesian Methods — 14 citations into it
• Statistical and Nonlinear Physics — 14 citations into it

Whom Wei Chen trusts overall

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

1. Diederik P. Kingma
2. Alex Krizhevsky
3. Laurent Dinh
4. Tim Salimans
5. Geoffrey E. Hinton
6. Michael F. Hutchinson
7. Yoshua Bengio
8. Max Welling
9. Ilya Sutskever
10. Radford M. Neal

Papers from Wei Chen's perspective

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

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

Their papers

• Promoting transparency and reproducibility in enhanced molecular simulations (2019) — 1,046 citations
• TO-FLOW: Efficient Continuous Normalizing Flows with Temporal Optimization adjoint with Moving Speed (2022) — 12 citations