Alexander Pashevich

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 226 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 45 citations into it; #25,175 of 35,345 by trust here, #23,731 by citations
• Computer Vision and Pattern Recognition — 40 citations into it; #15,454 of 21,575 by trust here, #15,529 by citations
• Natural Language Processing — 29 citations into it; #4,196 of 5,688 by trust here, #4,449 by citations
• Reinforcement Learning — 18 citations into it
• Multimodal Learning — 13 citations into it
• Model Architectures — 9 citations into it
• Robotics & Control — 6 citations into it

Whom Alexander Pashevich trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Ross B. Girshick
4. Alex Krizhevsky
5. Yoshua Bengio
6. Diederik P. Kingma
7. Shaoqing Ren
8. Ilya Sutskever
9. Oriol Vinyals
10. Yann LeCun

Who trusts Alexander Pashevich overall

1. Byeonghwi Kim
2. Pierre-Louis Guhur
3. So Yeon Min
4. Alessandro Suglia
5. Arsha Nagrani
6. Chan Hee Song
7. Shizhe Chen
8. Minhyuk Seo
9. Anthony Brohan
10. Devendra Singh Chaplot

Papers from Alexander Pashevich's perspective

Ordered by how strongly the researchers Alexander Pashevich 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Episodic Transformer for Vision-and-Language Navigation (2021) — 233 citations