John M. Jumper

Model Architectures · 2018–2024

A researcher in the Science corpus: 15 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Model Architectures — 22 citations into it

Whom John M. Jumper trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Daniel Müllner
4. Diederik P. Kingma
5. Andrew W. Senior
6. Alex Krizhevsky
7. Yoshua Bengio
8. X. Zhang
9. Yann LeCun
10. Ilya Sutskever

Who trusts John M. Jumper overall

1. Liisa Holm
2. Björn Wallner
3. Andriy Kryshtafovych
4. Robin Pearce
5. Minkyung Baek
6. R. Tejero
7. Zhuoran Qiao
8. Lim Heo
9. Jeffrey A. Ruffolo
10. Erik Nijkamp

Papers from John M. Jumper's perspective

Ordered by how strongly the researchers John M. Jumper 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. Attention is All you Need (Neural Information Processing Systems)
3. ImageNet classification with deep convolutional neural networks
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Going deeper with convolutions
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Highly accurate protein structure prediction with AlphaFold (2021) — 37,531 citations
• Improved protein structure prediction using potentials from deep learning (2020) — 2,936 citations
• Highly accurate protein structure prediction for the human proteome (2021) — 2,524 citations
• Accelerating Large Language Model Decoding with Speculative Sampling (2023) — 973 citations
• Protein structure prediction using multiple deep neural networks in the 13th Critical Assessment of Protein Structure Prediction (CASP13) (2019) — 268 citations
• Protein complex prediction with AlphaFold-Multimer (2021) — 3,230 citations
• Supporting Online Material Materials and Methods Figs. S1 to S10 Table S1 References Movies S1 to S3 Atomic-level Characterization of the Structural Dynamics of Proteins — 1,242 citations
• AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models (2021) — 3,102 citations
• Accurate structure prediction of biomolecular interactions with AlphaFold 3 (2024) — 12,322 citations
• Effective gene expression prediction from sequence by integrating long-range interactions (2021) — 1,222 citations
• Accurate calculation of side chain packing and free energy with applications to protein molecular dynamics (2018) — 35 citations
• Accurate proteome-wide missense variant effect prediction with AlphaMissense (2023) — 1,696 citations
• Structure of the decoy module of human glycoprotein 2 and uromodulin and its interaction with bacterial adhesin FimH (2022) — 24 citations
• Applying and improving AlphaFold at CASP14 (2021) — 354 citations
• A 7 D De novo structure prediction with deep learning based scoring