Andreea Gane

Artificial Intelligence · 2015–2020

A researcher in the Science corpus: 4 papers; trusts 137 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 100 citations into it; #20,458 of 35,345 by trust here, #3,842 by citations
• Computer Vision and Pattern Recognition — 71 citations into it; #12,947 of 21,575 by trust here, #2,926 by citations
• Natural Language Processing — 49 citations into it; #3,801 of 5,688 by trust here, #2,567 by citations
• Model Architectures — 31 citations into it; #2,157 of 2,278 by trust here, #513 by citations
• Generative Models — 23 citations into it
• Representation & Self-Supervised Learning — 21 citations into it
• Probabilistic & Bayesian Methods — 19 citations into it
• Signal Processing — 11 citations into it

Whom Andreea Gane trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Yoshua Bengio
4. Ruslan Salakhutdinov
5. Ronald J. Williams
6. Ilya Sutskever
7. Alex Krizhevsky
8. Tomas Mikolov
9. Oriol Vinyals
10. Yann LeCun

Who trusts Andreea Gane overall

1. Jason Aaron Edward Weston
2. Caglar Gulcehre
3. Antoine Bordes
4. A. P. Sarath Chandar
5. Kyunghyun Cho
6. Tri Dao
7. Emily Dinan
8. Yi Tay
9. Tom Young
10. Michał Jungiewicz

Papers from Andreea Gane's perspective

Ordered by how strongly the researchers Andreea Gane 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. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Rethinking Attention with Performers (2020) — 2,365 citations
• Evaluating Prerequisite Qualities for Learning End-to-End Dialog Systems (2015) — 202 citations
• The Variational Homoencoder: Learning to learn high capacity generative models from few examples (2018) — 70 citations
• Direct Optimization through arg max for Discrete Variational Auto-Encoder (2019) — 41 citations