Akosua Busia

Molecular Biology · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 66 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 31 citations into it
• Artificial Intelligence — 17 citations into it
• Computer Vision and Pattern Recognition — 12 citations into it
• Model Architectures — 11 citations into it
• Optimization & Training — 9 citations into it
• Computational Biology & Bioinformatics — 8 citations into it

Whom Akosua Busia trusts overall

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

1. Christian Szegedy
2. Ilya Sutskever
3. Diederik P. Kingma
4. Geoffrey E. Hinton
5. Sergey Ioffe
6. Kaiming He
7. Alex Krizhevsky
8. Nitish Srivastava
9. Oriol Vinyals
10. Heng Li

Papers from Akosua Busia's perspective

Ordered by how strongly the researchers Akosua Busia 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
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. ImageNet Large Scale Visual Recognition Challenge

Their papers

• A deep learning approach to pattern recognition for short DNA sequences (2018) — 59 citations
• Next-Step Conditioned Deep Convolutional Neural Networks Improve Protein Secondary Structure Prediction (2017) — 48 citations