Paola Cascante-Bonilla

Artificial Intelligence · 2020–2022

A researcher in the Science corpus: 2 papers; trusts 97 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 89 citations into it
• Computer Vision and Pattern Recognition — 70 citations into it
• Representation & Self-Supervised Learning — 31 citations into it
• Optimization & Training — 17 citations into it
• Model Architectures — 7 citations into it

Whom Paola Cascante-Bonilla trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Ilya Loshchilov
6. Diederik P. Kingma
7. Jia Deng
8. Yann LeCun
9. Ilya Sutskever
10. Ross B. Girshick

Who trusts Paola Cascante-Bonilla overall

1. Lihe Yang
2. Massih-Reza Amini
3. Vasilii Feofanov

Papers from Paola Cascante-Bonilla's perspective

Ordered by how strongly the researchers Paola Cascante-Bonilla 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. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet: A large-scale hierarchical image database
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• CODA-Prompt: COntinual Decomposed Attention-Based Prompting for Rehearsal-Free Continual Learning (2022) — 609 citations
• Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised Learning (2020) — 377 citations