Nikhil Rasiwasia
Computer Vision and Pattern Recognition · 2010–2014
A researcher in the Science corpus: 4 papers; trusts 236 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 46 citations into it; #8,410 of 21,575 by trust here, #5,941 by citations
- Artificial Intelligence — 15 citations into it; #19,168 of 35,345 by trust here, #31,361 by citations
- Representation & Self-Supervised Learning — 12 citations into it
- Statistics and Probability — 9 citations into it
- Multimodal Learning — 8 citations into it; #652 of 1,211 by trust here, #526 by citations
- Natural Language Processing — 8 citations into it
- Signal Processing — 8 citations into it
- Probabilistic & Bayesian Methods — 6 citations into it; #1,028 of 1,525 by trust here, #1,390 by citations
Whom Nikhil Rasiwasia trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David M. Blei
- Radford M. Neal
- Tom Minka
- David G. Lowe
- Li Fei-Fei
- Andrew Zisserman
- Geoffrey E. Hinton
- Michael I. Jordan
- Josef Sivic
- Yann LeCun
Who trusts Nikhil Rasiwasia overall
- Yuxin Peng
- Fan Zhang
- Kaiye Wang
- Yusuf Aytar
- Xiaohua Zhai
- C. V. Jawahar
- Cuicui Kang
- Bo Du
- Xing Xu
- Miaomiao Cheng
Papers from Nikhil Rasiwasia's perspective
Ordered by how strongly the researchers Nikhil Rasiwasia 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)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
Their papers
- A new approach to cross-modal multimedia retrieval (2010) — 1,376 citations
- On the Role of Correlation and Abstraction in Cross-Modal Multimedia Retrieval (2014) — 399 citations
- Cluster Canonical Correlation Analysis (2014) — 170 citations
- Latent Dirichlet Allocation Models for Image Classification (2013) — 99 citations