F. Chen

Molecular Biology · Cell · 2000–2021

A researcher in the Science corpus: 16 papers; trusts 77 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 137 citations into it; #12,147 of 17,773 by trust here, #5,137 by citations
• Artificial Intelligence — 51 citations into it; #33,226 of 35,345 by trust here, #13,544 by citations
• Computer Vision and Pattern Recognition — 41 citations into it; #20,354 of 21,575 by trust here, #9,305 by citations
• Renewable Energy, Sustainability and the Environment — 36 citations into it
• Materials Chemistry — 33 citations into it
• Representation & Self-Supervised Learning — 16 citations into it
• Optimization & Training — 13 citations into it
• Efficiency & Compression — 10 citations into it; #1,178 of 1,264 by trust here, #758 by citations

Whom F. Chen trusts overall

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

1. Alex Krizhevsky
2. Yann LeCun
3. Geoffrey E. Hinton
4. Diederik P. Kingma
5. Yoshua Bengio
6. Kaiming He
7. Karen Simonyan
8. Sergey Ioffe
9. Baharan Mirzasoleiman
10. Richard A. Dixon

Who trusts F. Chen overall

1. Ursula Pieper
2. Adrian M. Altenhoff
3. Sergey Dobretsov
4. K. Weitbrecht
5. Jue Ruan

Papers from F. Chen's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Learning Multiple Layers of Features from Tiny Images
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet: A large-scale hierarchical image database
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Training and Inference with Integers in Deep Neural Networks (2018) — 419 citations
• OrthoMCL-DB: querying a comprehensive multi-species collection of ortholog groups (2005) — 902 citations
• Experimental factors affecting PCR-based estimates of microbial species richness and evenness (2010) — 618 citations
• A complementary transposon tool kit for Drosophila melanogaster using P and piggyBac (2004) — 900 citations
• Mechanisms and Genes Involved in Germination Sensu Stricto (2007) — 103 citations
• Genomics of Secondary Metabolism in Populus: Interactions with Biotic and Abiotic Environments (2009) — 117 citations
• RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning (2021) — 112 citations
• The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution (2020) — 482 citations
• Pathogenic germline variants in 10,389 adult cancers (2018) — 734 citations
• Insights into Land Plant Evolution Garnered from the Marchantia polymorpha Genome. (2017) — 1,026 citations
• In situ self-transformation synthesis of g-C3N4-modified CdS heterostructure with enhanced photocatalytic activity (2015) — 158 citations
• Extensive sequencing of seven human genomes to characterize benchmark reference materials (2015) — 739 citations
• Identification of a haloalkaliphilic and thermostable cellulase with improved ionic liquid tolerance (2011) — 129 citations
• High‐Conductivity Poly(3,4‐ethylenedioxythiophene):Poly(styrene sulfonate) Film and Its Application in Polymer Optoelectronic Devices (2005) — 890 citations
• Bioactivity of bacterial strains isolated from marine biofilms in Hong Kong waters for the induction of larval settlement in the marine polychaete Hydroides elegans (2002) — 137 citations
• Gene expression prior to radicle emergence in imbibed tomato seeds. (2000) — 86 citations