D. Luan
Artificial Intelligence · 2019–2022
A researcher in the Science corpus: 4 papers; trusts 128 researchers and is trusted by 297 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 254 citations into it
- Natural Language Processing — 143 citations into it
- Computer Vision and Pattern Recognition — 119 citations into it
- Large Language Models — 48 citations into it; #23 of 799 by trust here, #41 by citations
- Representation & Self-Supervised Learning — 48 citations into it
- Model Architectures — 39 citations into it
Whom D. Luan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Ilya Sutskever
- Yoshua Bengio
- Alex Krizhevsky
- Kaiming He
- Diederik P. Kingma
- Alex Graves
- Yann LeCun
- Quoc V. Le
- Oriol Vinyals
Who trusts D. Luan overall
- Timo Schick
- Percy Liang
- Yejin Choi
- Hinrich Schütze
- Mohit Bansal
- Yi Tay
- Luke S. Zettlemoyer
- Kyunghyun Cho
- Eric Wallace
- Jianfeng Gao
Papers from D. Luan's perspective
Ordered by how strongly the researchers D. Luan trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- PaLM: Scaling Language Modeling with Pathways (2022) — 8,214 citations
- Show Your Work: Scratchpads for Intermediate Computation with Language Models (2021) — 1,075 citations
- Generative Pretraining From Pixels (2020) — 1,828 citations
- Language Models are Unsupervised Multitask Learners (2019) — 29,506 citations