Markus Hanselmann

Artificial Intelligence · 2017

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 21 citations into it; #20,717 of 35,345 by trust here, #23,731 by citations
• Safety, Robustness & Interpretability — 16 citations into it
• Computer Vision and Pattern Recognition — 8 citations into it

Whom Markus Hanselmann trusts overall

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

1. Alex Krizhevsky
2. Nicolas Papernot
3. Ian J. Goodfellow
4. Yehuda Koren
5. Christian Szegedy
6. Geoffrey E. Hinton
7. Yann LeCun
8. Ilya Sutskever
9. Patrick Drew McDaniel
10. Yoshua Bengio

Who trusts Markus Hanselmann overall

1. David Stutz
2. Daniel Jakubovitz
3. Matthias Hein
4. Cihang Xie

Papers from Markus Hanselmann's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Learning Multiple Layers of Features from Tiny Images
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Gradient-based learning applied to document recognition
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. Attention is All you Need (Neural Information Processing Systems)
9. Intriguing properties of neural networks
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Ensemble Methods as a Defense to Adversarial Perturbations Against Deep Neural Networks (2017) — 149 citations