Matthew McPartlon

Molecular Biology · 2020–2022

A researcher in the Science corpus: 2 papers; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 51 citations into it
• Computational Biology & Bioinformatics — 32 citations into it
• Materials Chemistry — 23 citations into it
• Model Architectures — 8 citations into it
• Computational Theory and Mathematics — 7 citations into it
• Artificial Intelligence — 6 citations into it

Whom Matthew McPartlon trusts overall

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

1. Diederik P. Kingma
2. Jimmy Ba
3. Razvan Pascanu
4. Georgii G. Krivov
5. Yoshua Bengio
6. Fabian B. Fuchs
7. Geoffrey E. Hinton
8. Thomas C. Bachlechner
9. Tomas Mikolov
10. Mohammed Alquraishi

Who trusts Matthew McPartlon overall

1. Namrata Anand

Papers from Matthew McPartlon's perspective

Ordered by how strongly the researchers Matthew McPartlon 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Attention is All you Need (Neural Information Processing Systems)
4. ImageNet classification with deep convolutional neural networks
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Improved protein structure prediction by deep learning irrespective of co-evolution information (2020) — 210 citations
• An end-to-end deep learning method for rotamer-free protein side-chain packing (2022) — 13 citations