Gaurav Rattan
Artificial Intelligence · 2015–2019
A researcher in the Science corpus: 3 papers; trusts 89 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 81 citations into it
- Graph Learning — 70 citations into it; #508 of 693 by trust here, #264 by citations
- Computer Vision and Pattern Recognition — 36 citations into it
- Computational Theory and Mathematics — 30 citations into it
- Molecular Biology — 26 citations into it
- Statistical and Nonlinear Physics — 21 citations into it
- Materials Chemistry — 15 citations into it
- Computational Chemistry & Drug Discovery — 11 citations into it
Whom Gaurav Rattan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Martin Grohe
- Diederik P. Kingma
- Christopher Morris
- Chih-Jen Lin
- Geoffrey E. Hinton
- Oriol Vinyals
- Rex Ying
- Yoshua Bengio
- Nino Shervashidze
- Nils M. Kriege
Who trusts Gaurav Rattan overall
Papers from Gaurav Rattan's perspective
Ordered by how strongly the researchers Gaurav Rattan 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)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- On the Power of Color Refinement (2015) — 48 citations
- Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddings (2019) — 185 citations
- Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks (2018) — 2,039 citations