Gianluca Corrado
Computer Vision and Pattern Recognition · 2023
A researcher in the Science corpus: 1 paper; trusts 24 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 44 citations into it
- Artificial Intelligence — 33 citations into it
- Generative Models — 23 citations into it
Whom Gianluca Corrado trusts
Their strongest outbound trust, strongest first, inferred from their citations.
- Jonathan Ho (in Computer Vision and Pattern Recognition)
- Ian J. Goodfellow (in Computer Vision and Pattern Recognition)
- Karen Simonyan (in Computer Vision and Pattern Recognition)
- Alex Krizhevsky (in Computer Vision and Pattern Recognition)
- Kaiming He (in Computer Vision and Pattern Recognition)
- Andrew Zisserman (in Computer Vision and Pattern Recognition)
- Antonio Torralba (in Computer Vision and Pattern Recognition)
- Ross B. Girshick (in Computer Vision and Pattern Recognition)
- Jeff Donahue (in Computer Vision and Pattern Recognition)
- Rob Fergus (in Computer Vision and Pattern Recognition)
Papers from Gianluca Corrado's perspective
Ordered by how strongly the researchers Gianluca Corrado trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- GENERATIVE ADVERSARIAL NETS
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Et al
- Language Models are Few-Shot Learners (Neural Information Processing Systems)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
Their papers
- GAIA-1: A Generative World Model for Autonomous Driving (2023) — 613 citations