Efi Kokiopoulou
Artificial Intelligence · 2019–2023
A researcher in the Science corpus: 4 papers; trusts 90 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 49 citations into it
- Computer Vision and Pattern Recognition — 33 citations into it
- Model Architectures — 22 citations into it
- Optimization & Training — 14 citations into it
- Representation & Self-Supervised Learning — 10 citations into it
- Efficiency & Compression — 9 citations into it
- Meta & Continual Learning — 9 citations into it
Whom Efi Kokiopoulou trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Barret Zoph
- Quoc V. Le
- Alex Krizhevsky
- Yoshua Bengio
- Kaiming He
- Yann LeCun
- Ronald J. Williams
- Ilya Sutskever
Who trusts Efi Kokiopoulou overall
Papers from Efi Kokiopoulou's perspective
Ordered by how strongly the researchers Efi Kokiopoulou 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)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Fast Task-Aware Architecture Inference (2019) — 18 citations
- Gumbel-Matrix Routing for Flexible Multi-task Learning (2019) — 13 citations
- Three Towers: Flexible Contrastive Learning with Pretrained Image Models (2023)
- Routing Networks with Co-training for Continual Learning (2020) — 15 citations