Mohammed Asif Khan

Molecular Biology · 2017

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 20 citations into it; #12,096 of 17,773 by trust here, #13,563 by citations

Whom Mohammed Asif Khan trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Anastasia Baryshnikova
4. Xavier Glorot
5. Emmanuel Boutet
6. Wyatt Travis Clark
7. Ronan Collobert
8. Yann LeCun
9. Predrag Radivojac
10. Pascale Gaudet

Who trusts Mohammed Asif Khan overall

1. Felipe Kenji Nakano
2. Nils Strodthoff
3. Yu Li

Papers from Mohammed Asif Khan's perspective

Ordered by how strongly the researchers Mohammed Asif Khan 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
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. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier (2017) — 471 citations