Maria R. Cervera

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 3 papers; trusts 106 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 142 citations into it
• Computer Vision and Pattern Recognition — 76 citations into it
• Meta & Continual Learning — 52 citations into it
• Model Architectures — 32 citations into it
• Probabilistic & Bayesian Methods — 32 citations into it
• Representation & Self-Supervised Learning — 31 citations into it
• Generative Models — 29 citations into it
• Optimization & Training — 26 citations into it

Whom Maria R. Cervera trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Yann LeCun
5. J. Urgen Schmidhuber
6. Alex Krizhevsky
7. Sepp Hochreiter
8. Alex Graves
9. Kaiming He
10. David John Cameron MacKay

Who trusts Maria R. Cervera overall

1. Gyuhak Kim

Papers from Maria R. Cervera's perspective

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

Their papers

• Posterior Meta-Replay for Continual Learning (2021) — 76 citations
• Continual learning in recurrent neural networks (2020) — 52 citations
• Continual Learning in Recurrent Neural Networks with Hypernetworks (2020) — 10 citations