J. Böhm

Representation & Self-Supervised Learning · 2020

A researcher in the Science corpus: 1 paper; trusts 24 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Representation & Self-Supervised Learning — 17 citations into it
• Computer Vision and Pattern Recognition — 15 citations into it
• Molecular Biology — 14 citations into it
• Artificial Intelligence — 11 citations into it

Whom J. Böhm trusts overall

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

1. L. V. D. van der Maaten
2. George C. Linderman
3. Dmitry Kobak
4. Geoffrey E. Hinton
5. Leland McInnes
6. Mikhail Belkin
7. Ronald R. Coifman
8. Michael U Gutmann
9. Ehsan Amid
10. Tomas Mikolov

Who trusts J. Böhm overall

1. Yingfan Wang
2. Cynthia Rudin
3. Ying-Fan Wang
4. Dmitry Kobak
5. Haiyang Huang

Papers from J. Böhm's perspective

Ordered by how strongly the researchers J. Böhm 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Learning Multiple Layers of Features from Tiny Images
8. ImageNet: A large-scale hierarchical image database
9. ImageNet Large Scale Visual Recognition Challenge
10. Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)

Their papers

• A Unifying Perspective on Neighbor Embeddings along the Attraction-Repulsion Spectrum (2020) — 26 citations