Maximilian Ilse

Computer Vision and Pattern Recognition · 2018–2023

A researcher in the Science corpus: 2 papers; trusts 30 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 55 citations into it; #8,104 of 21,575 by trust here, #9,872 by citations
• Artificial Intelligence — 54 citations into it; #12,201 of 35,345 by trust here, #14,438 by citations
• Natural Language Processing — 10 citations into it
• Model Architectures — 9 citations into it

Whom Maximilian Ilse trusts overall

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

1. Charles Ruizhongtai Qi
2. Yann LeCun
3. Yoshua Bengio
4. Dzmitry Bahdanau
5. Geoffrey E. Hinton
6. Diederik P. Kingma
7. L. Eon Bottou
8. Alex Krizhevsky
9. Yann Dauphin
10. Kyunghyun Cho

Who trusts Maximilian Ilse overall

1. Richard J. Chen
2. Ming Y. Lu
3. Fanjie Kong
4. J. A. van der Laak
5. Chetan L. Srinidhi
6. Bin Li
7. Jiawen Yao
8. Mohammed Adnan
9. Juho Lee
10. Zhucheng Shao

Papers from Maximilian Ilse's perspective

Ordered by how strongly the researchers Maximilian Ilse 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. Attention is All you Need (Neural Information Processing Systems)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Attention-based Deep Multiple Instance Learning (2018) — 2,646 citations
• Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing (2023) — 304 citations