Zhewei Wei
Artificial Intelligence · 2020–2023
A researcher in the Science corpus: 4 papers; trusts 56 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 146 citations into it; #26,956 of 35,345 by trust here, #9,760 by citations
- Computer Vision and Pattern Recognition — 59 citations into it
- Graph Learning — 38 citations into it; #667 of 693 by trust here, #443 by citations
- Molecular Biology — 36 citations into it
- Statistical and Nonlinear Physics — 22 citations into it
- Representation & Self-Supervised Learning — 21 citations into it
- Information Systems — 20 citations into it; #8,443 of 8,771 by trust here, #3,315 by citations
- Computational Chemistry & Drug Discovery — 12 citations into it
Whom Zhewei Wei trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Johannes Klicpera
- Diederik P. Kingma
- Kaiming He
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Krizhevsky
- Yann LeCun
- Prithviraj Sen
- Max Welling
- Matthias Fey
Who trusts Zhewei Wei overall
Papers from Zhewei Wei's perspective
Ordered by how strongly the researchers Zhewei Wei trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- A survey on large language model based autonomous agents (2023) — 3,361 citations
- Simple and Deep Graph Convolutional Networks (2020) — 1,998 citations
- Uni-Mol: A Universal 3D Molecular Representation Learning Framework (2023) — 625 citations
- BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation (2021) — 355 citations