Amil Merchant

Artificial Intelligence · 2020–2023

A researcher in the Science corpus: 3 papers; trusts 50 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 69 citations into it
• Natural Language Processing — 48 citations into it
• Materials Chemistry — 42 citations into it
• Computer Vision and Pattern Recognition — 22 citations into it
• Evaluation & Benchmarks — 18 citations into it
• Model Architectures — 13 citations into it

Whom Amil Merchant trusts overall

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

1. Elena Voita
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. J. Behler
5. Yoshua Bengio
6. Christopher D. Manning
7. Ilya Sutskever
8. Alex Krizhevsky
9. Yann LeCun
10. Kaiming He

Who trusts Amil Merchant overall

1. Zixuan Ke
2. Charles Lovering
3. Kushal Tirumala
4. Tianyi Zhang
5. Bing Liu
6. Hu Xu
7. Rohan Jha
8. Georgios Chochlakis
9. Aram H. Markosyan
10. Felix Wu

Papers from Amil Merchant's perspective

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

1. Attention is All you Need (Neural Information Processing Systems)
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Long Short-Term Memory
5. ImageNet classification with deep convolutional neural networks
6. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
7. ImageNet: A large-scale hierarchical image database
8. Gradient-based learning applied to document recognition
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Scaling deep learning for materials discovery (2023) — 1,483 citations
• An autonomous laboratory for the accelerated synthesis of inorganic materials (2023) — 797 citations
• What Happens To BERT Embeddings During Fine-tuning? (2020) — 222 citations