Ehsan Elhamifar
Computer Vision and Pattern Recognition · 2009–2021
A researcher in the Science corpus: 7 papers; trusts 420 researchers and is trusted by 421 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 131 citations into it; #1,980 of 21,575 by trust here, #4,048 by citations
- Computational Mechanics — 80 citations into it; #178 of 10,001 by trust here, #609 by citations
- Artificial Intelligence — 67 citations into it; #25,078 of 35,345 by trust here, #21,878 by citations
- Signal Processing — 34 citations into it
- Representation & Self-Supervised Learning — 27 citations into it
- Statistics and Probability — 24 citations into it
- Media Technology — 15 citations into it; #707 of 3,621 by trust here, #1,646 by citations
- Applied Mathematics — 14 citations into it
Whom Ehsan Elhamifar trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- E.J. Candes
- David L. Donoho
- René Vidal
- Robert Tibshirani
- Paul Tseng
- K. Kanatani
- Guangcan Liu
- Yi Ma
- Roberto Tron
- Andrew Y. Ng
Who trusts Ehsan Elhamifar overall
- René Vidal
- Changqing Zhang
- Guangcan Liu
- Zhouchen Lin
- M. Soltanolkotabi
- Paolo Favaro
- Chong You
- Lei Zhang
- Ran He
- Guillermo Sapiro
Papers from Ehsan Elhamifar's perspective
Ordered by how strongly the researchers Ehsan Elhamifar trusts endorse each paper. Same corpus, a different order for every researcher.
- 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)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Sparse subspace clustering (2009) — 1,495 citations
- Sparse Subspace Clustering: Algorithm, Theory, and Applications (2012) — 2,496 citations
- See all by looking at a few: Sparse modeling for finding representative objects (2012) — 405 citations
- Robust Subspace Clustering (2013) — 376 citations
- Open-Vocabulary Instance Segmentation via Robust Cross-Modal Pseudo-Labeling (2021) — 112 citations
- Sparse Subspace Clustering: Algorithm, Theory, and Applications (2013) — 651 citations
- Sparse Manifold Clustering and Embedding (2011) — 304 citations