Anna C. Belkina
Molecular Biology · 2012–2019
A researcher in the Science corpus: 5 papers; trusts 8 researchers and is trusted by 8 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 70 citations into it; #12,077 of 17,773 by trust here, #11,818 by citations
- Immunology — 60 citations into it; #679 of 2,160 by trust here, #2,008 by citations
- Oncology — 24 citations into it; #500 of 1,698 by trust here, #1,608 by citations
- Biophysics — 23 citations into it; #842 of 1,196 by trust here, #850 by citations
- Computer Vision and Pattern Recognition — 18 citations into it
- Representation & Self-Supervised Learning — 18 citations into it; #2,603 of 3,145 by trust here, #2,805 by citations
- Artificial Intelligence — 13 citations into it
Whom Anna C. Belkina trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- E. Wherry
- Mario Roederer
- L. V. D. van der Maaten
- George C. Linderman
- Martin Wattenberg
- Nicola Pezzotti
- David Chan
- Sean Bendall
- Dmitry Kobak
- Lukas M. Weber
Who trusts Anna C. Belkina overall
- Pavlin Gregor Policar
- Chris Ciccolella
- Yingfan Wang
- Martin Stražar
- Dmitry Kobak
- Mekhail Mustak
- R. Anno
- Blaz Zupan
- Richard L. Halpert
- Miroslav Kratochvı́l
Papers from Anna C. Belkina's perspective
Ordered by how strongly the researchers Anna C. Belkina trusts endorse each paper. Same corpus, a different order for every researcher.
- Visualizing Data using t-SNE
- Gradient-based learning applied to document recognition
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- Attention is All you Need (Neural Information Processing Systems)
- Going deeper with convolutions
- ImageNet: A large-scale hierarchical image database
Their papers
- Automated Optimal Parameters for T-Distributed Stochastic Neighbor Embedding Improve Visualization and Allow Analysis of Large Datasets (2018) — 18 citations
- Automated optimized parameters for T-distributed stochastic neighbor embedding improve visualization and analysis of large datasets (2019) — 553 citations
- BET domain co-regulators in obesity, inflammation and cancer (2012) — 696 citations
- Multivariate Computational Analysis of Gamma Delta T Cell Inhibitory Receptor Signatures Reveals the Divergence of Healthy and ART-Suppressed HIV+ Aging (2018) — 36 citations
- OMIP‐037: 16‐color panel to measure inhibitory receptor signatures from multiple human immune cell subsets (2017) — 21 citations