Kamal Choudhary

Materials Chemistry · 2018–2021

A researcher in the Science corpus: 3 papers; trusts 3 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Materials Chemistry — 129 citations into it; #7,216 of 11,513 by trust here, #9,387 by citations
• Artificial Intelligence — 45 citations into it
• Catalysis — 14 citations into it

Whom Kamal Choudhary trusts overall

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

1. Eric R. Ziegel
2. Tian Xie
3. Geoffrey E. Hinton
4. J. Behler
5. Yoshua Bengio
6. Logan T. Ward
7. Yann LeCun
8. Alex Krizhevsky
9. Diederik P. Kingma
10. Keyulu Xu

Who trusts Kamal Choudhary overall

1. Chi Chen
2. Brian L. DeCost
3. Shyue Ping Ong
4. Weike Ye

Papers from Kamal Choudhary's perspective

Ordered by how strongly the researchers Kamal Choudhary 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Learning Multiple Layers of Features from Tiny Images
10. Going deeper with convolutions

Their papers

• Atomistic Line Graph Neural Network for improved materials property predictions (2021) — 757 citations
• Machine learning with force-field inspired descriptors for materials: fast screening and mapping energy landscape (2018) — 144 citations
• Recent advances and applications of deep learning methods in materials science (2021) — 995 citations