Pavlin Gregor Policar
Molecular Biology · 2019
A researcher in the Science corpus: 3 papers; trusts 19 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 48 citations into it; #7,656 of 17,773 by trust here, #13,563 by citations
- Representation & Self-Supervised Learning — 21 citations into it; #2,202 of 3,145 by trust here, #2,691 by citations
- Artificial Intelligence — 14 citations into it
- Biophysics — 14 citations into it
- Computer Vision and Pattern Recognition — 14 citations into it
- Immunology — 7 citations into it
- Computer Networks and Communications — 6 citations into it
Whom Pavlin Gregor Policar trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- L. V. D. van der Maaten
- Leland McInnes
- Robert A. Jacobs
- John Healy
- Anna C. Belkina
- Mikhail Belkin
- Geoffrey E. Hinton
- Martin Stražar
- Yury Malkov
- Vladimir Yu. Kiselev
Who trusts Pavlin Gregor Policar overall
Papers from Pavlin Gregor Policar's perspective
Ordered by how strongly the researchers Pavlin Gregor Policar trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Visualizing Data using t-SNE
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
- ImageNet: A large-scale hierarchical image database
Their papers
- openTSNE: a modular Python library for t-SNE dimensionality reduction and embedding (2019) — 231 citations
- Embedding to reference t-SNE space addresses batch effects in single-cell classification (2019) — 36 citations
- scOrange—a tool for hands-on training of concepts from single-cell data analytics (2019) — 13 citations