Gatsby
Artificial Intelligence · 2010
A researcher in the Science corpus: 2 papers; trusts 24 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 15 citations into it; #26,755 of 35,345 by trust here, #28,481 by citations
- Probabilistic & Bayesian Methods — 9 citations into it
- Natural Language Processing — 6 citations into it
- Statistics and Probability — 6 citations into it; #10,008 of 12,932 by trust here, #8,740 by citations
Whom Gatsby trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Radford M. Neal
- Michael I. Jordan
- Yee Whye Teh
- David M. Blei
- Lawrence R. Rabiner
- T. Griffiths
- Li Fei-Fei
- Erik B. Sudderth
- Geoffrey E. Hinton
- Aude Oliva
Who trusts Gatsby overall
Papers from Gatsby's perspective
Ordered by how strongly the researchers Gatsby trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- 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)