Dawid J. Kopiczko

Artificial Intelligence · 2023

A researcher in the Science corpus: 1 paper; trusts 70 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 22 citations into it
• Computer Vision and Pattern Recognition — 20 citations into it
• Efficiency & Compression — 8 citations into it
• Large Language Models — 8 citations into it

Whom Dawid J. Kopiczko trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Geoffrey E. Hinton
4. Andrew Zisserman
5. Yoshua Bengio
6. Jia Deng
7. Diederik P. Kingma
8. Ilya Sutskever
9. Yann LeCun
10. Alec Radford

Papers from Dawid J. Kopiczko's perspective

Ordered by how strongly the researchers Dawid J. Kopiczko 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. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
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. Learning Multiple Layers of Features from Tiny Images
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• VeRA: Vector-based Random Matrix Adaptation (2023) — 345 citations