D. Kondratyuk

Computer Vision and Pattern Recognition · with Yang · 2019–2023

A researcher in the Science corpus: 2 papers; trusts 94 researchers and is trusted by 44 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 64 citations into it
• Artificial Intelligence — 49 citations into it; #4,182 of 35,345 by trust here, #21,878 by citations
• Natural Language Processing — 29 citations into it
• Large Language Models — 14 citations into it
• Evaluation & Benchmarks — 10 citations into it
• Model Architectures — 8 citations into it
• Representation & Self-Supervised Learning — 8 citations into it

Whom D. Kondratyuk trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Diederik P. Kingma
4. Jesse Vig
5. Ilya Sutskever
6. Christopher D. Manning
7. Alex Krizhevsky
8. Jacob Devlin
9. Kaiming He
10. Yann LeCun

Who trusts D. Kondratyuk overall

1. Goran Glavas
2. Pedro Ortiz Suarez
3. Ivan Vulic
4. Anne Lauscher
5. Akari Asai
6. Ricardo Rei
7. Ahmet Üstün
8. Fajri Koto
9. Adithya Pratapa
10. Antti Virtanen

Papers from D. Kondratyuk's perspective

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

Their papers

• 75 Languages, 1 Model: Parsing Universal Dependencies Universally (2019) — 294 citations
• VideoPoet: A Large Language Model for Zero-Shot Video Generation (2023) — 521 citations