Christos Baziotis

Artificial Intelligence · 2017–2019

A researcher in the Science corpus: 3 papers; trusts 159 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 72 citations into it; #12,843 of 35,345 by trust here, #13,353 by citations
• Natural Language Processing — 52 citations into it; #2,859 of 5,688 by trust here, #3,421 by citations
• Computer Vision and Pattern Recognition — 20 citations into it
• Model Architectures — 19 citations into it
• Representation & Self-Supervised Learning — 12 citations into it
• Optimization & Training — 8 citations into it
• Evaluation & Benchmarks — 6 citations into it

Whom Christos Baziotis trusts overall

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

1. Yoshua Bengio
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Ilya Sutskever
5. Sepp Hochreiter
6. Jimmy Ba
7. Alex Krizhevsky
8. Yann LeCun
9. Oriol Vinyals
10. Kyunghyun Cho

Who trusts Christos Baziotis overall

1. Francisca Adoma Acheampong
2. Timo Schick
3. Alexandra Chronopoulou
4. Peter J. Liu
5. Ankush Chatterjee
6. Leo Laugier
7. Leonard Adolphs
8. Alexander R. Fabbri
9. Sebastian Gehrmann
10. Henry Nunoo-Mensah

Papers from Christos Baziotis's perspective

Ordered by how strongly the researchers Christos Baziotis 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. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• An Embarrassingly Simple Approach for Transfer Learning from Pretrained Language Models (2019) — 143 citations
• SEQˆ3: Differentiable Sequence-to-Sequence-to-Sequence Autoencoder for Unsupervised Abstractive Sentence Compression (2019) — 86 citations
• DataStories at SemEval-2017 Task 4: Deep LSTM with Attention for Message-level and Topic-based Sentiment Analysis (2017) — 484 citations