Ratul Chowdhury

Molecular Biology · 2021–2022

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 65 citations into it
• Materials Chemistry — 32 citations into it
• Computational Biology & Bioinformatics — 27 citations into it

Whom Ratul Chowdhury trusts overall

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

1. Mohammed Alquraishi
2. Joshua Meier
3. Naomi Fox
4. Alexander Rives
5. Ashish Vaswani
6. Roshan Rao
7. Rasko Leinonen
8. Ali Madani
9. Yang Zhang
10. Dong Xu

Who trusts Ratul Chowdhury overall

1. Jeffrey A. Ruffolo
2. Patrick Bryant
3. Lee-Shin Chu
4. Zhenyu Yang
5. Zhuoran Qiao
6. Kevin E. Wu
7. Jue Wang
8. Kevin Kaichuang Yang
9. Inigo Barrio Hernandez
10. Sai Pooja Mahajan

Papers from Ratul Chowdhury's perspective

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

1. Attention is All you Need (Neural Information Processing Systems)
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. 5分で分かる!? 有名論文ナナメ読み：Jacob Devlin et al. : BERT : Pre-training of Deep Bidirectional Transformers for Language Understanding
6. ImageNet classification with deep convolutional neural networks
7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. GENERATIVE ADVERSARIAL NETS
9. Gradient-based learning applied to document recognition
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Single-sequence protein structure prediction using language models from deep learning (2021) — 64 citations
• Single-sequence protein structure prediction using language models and deep learning (2022) — 358 citations