Mohammad R. K. Mofrad
Molecular Biology · 2015–2019
A researcher in the Science corpus: 3 papers; trusts 12 researchers and is trusted by 37 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 51 citations into it; #959 of 17,773 by trust here, #7,911 by citations
- Artificial Intelligence — 11 citations into it
- Computational Biology & Bioinformatics — 11 citations into it; #107 of 660 by trust here, #473 by citations
- Natural Language Processing — 10 citations into it
- Representation & Self-Supervised Learning — 10 citations into it; #711 of 3,145 by trust here, #1,866 by citations
Whom Mohammad R. K. Mofrad trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Who trusts Mohammad R. K. Mofrad overall
- Michael Heinzinger
- Ahmed Elnaggar
- Kevin Kaichuang Yang
- Claudio Mirabello
- Z. Li
- Fangping Wan
- Konstantin Weissenow
- Sabrina Jaeger
- Seonwoo Min
- Ehsaneddin Asgari
Papers from Mohammad R. K. Mofrad's perspective
Ordered by how strongly the researchers Mohammad R. K. Mofrad trusts endorse each paper. Same corpus, a different order for every researcher.
- Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Neural Machine Translation of Rare Words with Subword Units
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics (2015) — 389 citations
- Probabilistic variable-length segmentation of protein sequences for discriminative motif discovery (DiMotif) and sequence embedding (ProtVecX) (2018) — 76 citations
- The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens (2019) — 434 citations