Amr M. Alexandari
Molecular Biology · 2017–2021
A researcher in the Science corpus: 3 papers; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 301 citations into it
- Artificial Intelligence — 203 citations into it
- Computer Vision and Pattern Recognition — 90 citations into it
- Safety, Robustness & Interpretability — 44 citations into it
- Optimization & Training — 19 citations into it
- Management Science and Operations Research — 5 citations into it
Whom Amr M. Alexandari trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Avanti Shrikumar
- Diederik P. Kingma
- Xavier Glorot
- Peyton Greenside
- David R. Kelley
- Yoshua Bengio
- Jimmy Ba
- Anshul B Kundaje
- M. Corces
- Jasper Snoek
Papers from Amr M. Alexandari's perspective
Ordered by how strongly the researchers Amr M. Alexandari trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Opportunities and obstacles for deep learning in biology and medicine (2017) — 2,030 citations
- Base-resolution models of transcription factor binding reveal soft motif syntax (2021) — 562 citations
- Separable Fully Connected Layers Improve Deep Learning Models For Genomics (2017) — 12 citations