Carlo Gatta
Computer Vision and Pattern Recognition · 2003–2015
A researcher in the Science corpus: 4 papers; trusts 280 researchers and is trusted by 814 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 50 citations into it; #1,552 of 21,575 by trust here, #1,112 by citations
- Artificial Intelligence — 30 citations into it; #3,056 of 35,345 by trust here, #1,602 by citations
- Representation & Self-Supervised Learning — 22 citations into it
- Media Technology — 13 citations into it; #994 of 3,621 by trust here, #910 by citations
- Optimization & Training — 10 citations into it
- Model Architectures — 9 citations into it; #335 of 2,278 by trust here, #178 by citations
- Signal Processing — 7 citations into it
- Generative Models — 5 citations into it
Whom Carlo Gatta trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yann LeCun
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Krizhevsky
- Andrew Y. Ng
- Adam Coates
- Marc'Aurelio Ranzato
- Honglak Lee
- Koray Kavukcuoglu
- Diederik P. Kingma
Who trusts Carlo Gatta overall
- Vijay Badrinarayanan
- Francesco Visin
- Yoshua Bengio
- Simon Jégou
- Jian Kang
- Gong Cheng
- Adriana Romero
- Dacheng Tao
- Zhiqiang Shen
- Alex Kendall
Papers from Carlo Gatta's perspective
Ordered by how strongly the researchers Carlo Gatta 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
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- 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
- FitNets: Hints for Thin Deep Nets (2014) — 4,770 citations
- Unrolling Loopy Top-Down Semantic Feedback in Convolutional Deep Networks (2014) — 38 citations
- A new algorithm for unsupervised global and local color correction (2003) — 359 citations
- Unsupervised Deep Feature Extraction for Remote Sensing Image Classification (2015) — 717 citations