Ramon Sanabria

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 4 papers; trusts 236 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 57 citations into it; #33,823 of 35,345 by trust here, #14,181 by citations
• Computer Vision and Pattern Recognition — 54 citations into it
• Natural Language Processing — 32 citations into it
• Multimodal Learning — 28 citations into it; #1,192 of 1,211 by trust here, #821 by citations
• Model Architectures — 8 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Ramon Sanabria trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Kaiming He
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Alex Krizhevsky
6. Desmond Elliott
7. Dzmitry Bahdanau
8. Sepp Hochreiter
9. Ilya Sutskever
10. Ross B. Girshick

Who trusts Ramon Sanabria overall

1. Elad Amrani
2. Antoine Miech
3. Shruti Palaskar
4. Rami Ben-Ari
5. Yasufumi Moriya
6. Tiezheng Yu
7. Florian Metze
8. Ha Nguyen
9. Nils Holzenberger
10. Hirofumi Inaguma

Papers from Ramon Sanabria's perspective

Ordered by how strongly the researchers Ramon Sanabria trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Grounding Object Detections With Transcriptions (2019) — 6 citations
• How2: A Large-scale Dataset for Multimodal Language Understanding (2018) — 326 citations
• Sequence-Based Multi-Lingual Low Resource Speech Recognition (2018) — 101 citations
• Looking Enhances Listening: Recovering Missing Speech Using Images (2020) — 15 citations