Andy M. Lau
Molecular Biology · 2018–2022
A researcher in the Science corpus: 4 papers; trusts 20 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 84 citations into it
- Computational Biology & Bioinformatics — 49 citations into it
- Materials Chemistry — 25 citations into it
- Spectroscopy — 13 citations into it
- Computational Theory and Mathematics — 7 citations into it
Whom Andy M. Lau trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Mohammed Alquraishi
- Yoav Benjamini
- Yang Zhang
- Sean R. Eddy
- Shaun M. Kandathil
- Jeffrey Skolnick
- Y. Hochberg
- A. Brunger
- Joe G. Greener
- Ashish Vaswani
Papers from Andy M. Lau's perspective
Ordered by how strongly the researchers Andy M. Lau trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Ultrafast end-to-end protein structure prediction enables high-throughput exploration of uncharacterized proteins (2022) — 40 citations
- Direct protein-lipid interactions shape the conformational landscape of secondary transporters (2018) — 129 citations
- Deuteros 2.0: peptide-level significance testing of data from hydrogen deuterium exchange mass spectrometry (2020) — 91 citations
- Deep learning-based prediction of protein structure using learned representations of multiple sequence alignments (2020) — 13 citations