Maximilian Mumme

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 17 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 12 citations into it; #11,808 of 35,345 by trust here, #12,387 by citations
• Graph Learning — 10 citations into it; #278 of 693 by trust here, #307 by citations
• Representation & Self-Supervised Learning — 5 citations into it

Whom Maximilian Mumme trusts overall

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

1. Diederik P. Kingma
2. Eric R. Ziegel
3. Aleksandar Bojchevski
4. Thomas Kipf
5. Galileo Namata
6. Geoffrey E. Hinton
7. Yoshua Bengio
8. Jimmy Ba
9. Johannes Klicpera
10. Max Welling

Who trusts Maximilian Mumme overall

1. Johannes Klicpera
2. Lingxiao Zhao
3. Xiyuan Wang
4. Dongkwan Kim
5. Hongwei Wang
6. Erlin Pan
7. Benjamin Paul Chamberlain
8. Matthias Fey
9. Benedek Rozemberczki
10. Yuhui Ding

Papers from Maximilian Mumme's perspective

Ordered by how strongly the researchers Maximilian Mumme trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Pitfalls of Graph Neural Network Evaluation (2018) — 1,809 citations