Pinar Yanardag
Computer Vision and Pattern Recognition · with Vishwanathan · 2015–2021
A researcher in the Science corpus: 3 papers; trusts 97 researchers and is trusted by 66 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 41 citations into it
- Generative Models — 29 citations into it
- Graph Learning — 20 citations into it; #89 of 693 by trust here, #183 by citations
- Artificial Intelligence — 14 citations into it; #4,151 of 35,345 by trust here, #8,210 by citations
- Natural Language Processing — 11 citations into it
- Representation & Self-Supervised Learning — 10 citations into it
- Computational Chemistry & Drug Discovery — 8 citations into it
- Statistical Learning Theory — 7 citations into it
Whom Pinar Yanardag trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Karsten M. Borgwardt
- Nino Shervashidze
- Alex Smola
- Yee Whye Teh
- J. Ramon
- Thomas Gärtner
- Stanley F. Chen
- Reinhard Kneser
- David Haussler
- S. V. N. Vishwanathan
Who trusts Pinar Yanardag overall
- Christopher Morris
- Nils M. Kriege
- Giannis Nikolentzos
- Haifeng Jin
- Rex Ying
- Petra Mutzel
- Saurabh Verma
- Yunsheng Bai
- Annamalai Narayanan
- Gaurav Rattan
Papers from Pinar Yanardag's perspective
Ordered by how strongly the researchers Pinar Yanardag 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Deep Graph Kernels (2015) — 1,512 citations
- StyleMC: Multi-Channel Based Fast Text-Guided Image Generation and Manipulation (2021) — 76 citations
- A Structural Smoothing Framework For Robust Graph Comparison (2015) — 69 citations