B. Bhinder

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 21 citations into it
• Molecular Biology — 19 citations into it
• Radiology, Nuclear Medicine and Imaging — 16 citations into it
• Computational Theory and Mathematics — 13 citations into it
• Computer Vision and Pattern Recognition — 5 citations into it
• Materials Chemistry — 5 citations into it

Whom B. Bhinder trusts overall

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

1. Nicola De Cao
2. Anika Cheerla
3. Łukasz Maziarka
4. Andre Esteva
5. B. Kuenzi
6. Thomas Kipf
7. Rikiya Yamashita
8. Olivier Gevaert
9. Xinggang Wang
10. Jakob Nikolas Kather

Papers from B. Bhinder's perspective

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

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

Their papers

• Artificial Intelligence in Cancer Research and Precision Medicine (2021) — 516 citations