Amit Kumar Saxena

Artificial Intelligence · 2017

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 20 citations into it
• Information Systems — 12 citations into it
• Statistical and Nonlinear Physics — 6 citations into it

Whom Amit Kumar Saxena trusts overall

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

1. Simon S. Haykin
2. Ulrike von Luxburg
3. Witold Pedrycz
4. Anil K. Jain
5. Rui Xu
6. Jianbo Shi
7. Geoffrey J. McLachlan
8. Raymond T. Ng
9. Julia Handl
10. George Siemens

Who trusts Amit Kumar Saxena overall

1. Zhaoyi Xu
2. Joseph Homer Saleh

Papers from Amit Kumar Saxena's perspective

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

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

Their papers

• A review of clustering techniques and developments (2017) — 1,203 citations