Jonas Oppenlaender

Computer Vision and Pattern Recognition · 2022

A researcher in the Science corpus: 2 papers; trusts 51 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 16 citations into it
• Artificial Intelligence — 14 citations into it
• Generative Models — 6 citations into it
• Large Language Models — 6 citations into it
• Prompting & Reasoning — 5 citations into it

Whom Jonas Oppenlaender trusts overall

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

1. Prafulla Dhariwal
2. James C. Kaufman
3. Robin Rombach
4. Katherine Crowson
5. John R. Searle
6. Xintao Wang
7. R. Beghetto
8. Laria Reynolds
9. Vivian Liu
10. Alex Nichol

Who trusts Jonas Oppenlaender overall

1. Leonardo Banh

Papers from Jonas Oppenlaender's perspective

Ordered by how strongly the researchers Jonas Oppenlaender 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. ImageNet Large Scale Visual Recognition Challenge
7. GENERATIVE ADVERSARIAL NETS
8. Long Short-Term Memory
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Gradient-based learning applied to document recognition

Their papers

• Prompt Engineering for Text-Based Generative Art (2022) — 41 citations
• The Creativity of Text-to-Image Generation (2022) — 300 citations