Milan Mossé

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 1 paper; trusts 183 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 43 citations into it
• Artificial Intelligence — 38 citations into it
• Representation & Self-Supervised Learning — 35 citations into it
• Large Language Models — 6 citations into it

Whom Milan Mossé trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Ross B. Girshick
5. Yoshua Bengio
6. Diederik P. Kingma
7. Karen Simonyan
8. Nitish Srivastava
9. Yann LeCun
10. Ilya Sutskever

Papers from Milan Mossé's perspective

Ordered by how strongly the researchers Milan Mossé 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. ImageNet: A large-scale hierarchical image database
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. Gradient-based learning applied to document recognition
8. ImageNet Large Scale Visual Recognition Challenge
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Conditional Negative Sampling for Contrastive Learning of Visual Representations (2020) — 91 citations