Fabio Maria Carlucci
Artificial Intelligence · 2017–2019
A researcher in the Science corpus: 4 papers; trusts 588 researchers and is trusted by 28 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 98 citations into it; #34,531 of 35,345 by trust here, #13,353 by citations
- Computer Vision and Pattern Recognition — 98 citations into it; #6,664 of 21,575 by trust here, #5,333 by citations
- Representation & Self-Supervised Learning — 55 citations into it; #1,567 of 3,145 by trust here, #1,430 by citations
- Model Architectures — 11 citations into it
- Optimization & Training — 11 citations into it
- Neural Architecture Search & AutoML — 9 citations into it; #120 of 283 by trust here, #191 by citations
- Radiology, Nuclear Medicine and Imaging — 9 citations into it; #874 of 3,265 by trust here, #1,923 by citations
- Cancer Research — 8 citations into it
Whom Fabio Maria Carlucci trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Yann LeCun
- Diederik P. Kingma
- Yoshua Bengio
- Kaiming He
- Ilya Sutskever
- Ross B. Girshick
- Jia Deng
- Trevor Darrell
Who trusts Fabio Maria Carlucci overall
- Kaiyang Zhou
- Garrett Wilson
- Hyeonseob Nam
- Jonathan Munro
- Massimiliano Mancini
- Haohan Wang
- Yanbei Chen
- Jian Liang
- Yu Sun
- Yongxin Yang
Papers from Fabio Maria Carlucci's perspective
Ordered by how strongly the researchers Fabio Maria Carlucci 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)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- 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
- Domain Generalization by Solving Jigsaw Puzzles (2019) — 952 citations
- AutoDIAL: Automatic Domain Alignment Layers (2017) — 335 citations
- NAS evaluation is frustratingly hard (2019) — 181 citations
- Agnostic Domain Generalization (2018) — 16 citations