Shunhua Jiang

Artificial Intelligence · 2017

A researcher in the Science corpus: 1 paper; trusts 14 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 13 citations into it; #31,504 of 35,345 by trust here, #28,481 by citations
• Optimization & Training — 12 citations into it; #2,432 of 2,601 by trust here, #2,259 by citations
• Model Architectures — 6 citations into it

Whom Shunhua Jiang trusts overall

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

1. Sepp Hochreiter
2. Yutian Chen
3. J. Urgen Schmidhuber
4. Ke Li
5. Neal Parikh
6. Geoffrey E. Hinton
7. Diederik P. Kingma
8. Djork-Arné Clevert
9. Matthew W. Hoffman
10. Jitendra Malik

Who trusts Shunhua Jiang overall

1. Luke Metz
2. Risto Vuorio
3. Tianlong Chen

Papers from Shunhua Jiang's perspective

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

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

Their papers

• Learning Gradient Descent: Better Generalization and Longer Horizons (2017) — 120 citations