Georgios Kaissis

Artificial Intelligence · 2017–2023

A researcher in the Science corpus: 6 papers; trusts 234 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 187 citations into it; #31,593 of 35,345 by trust here, #9,760 by citations
• Computer Vision and Pattern Recognition — 115 citations into it
• Representation & Self-Supervised Learning — 34 citations into it
• Privacy & Security — 19 citations into it
• Optimization & Training — 12 citations into it
• Federated & Distributed Learning — 11 citations into it

Whom Georgios Kaissis trusts overall

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

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

Who trusts Georgios Kaissis overall

1. Qinbin Li
2. Xuefei Yin
3. Jakob Mokander
4. Mohammed Adnan
5. Shaoting Zhang
6. Bingsheng He
7. Yanming Zhu
8. Jonas Schuett
9. Shivam Kalra

Papers from Georgios Kaissis's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• The Liver Tumor Segmentation Benchmark (LiTS) (2019) — 1,500 citations
• Secure, privacy-preserving and federated machine learning in medical imaging (2020) — 1,361 citations
• FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare (2023) — 491 citations
• Joint Learning of Localized Representations from Medical Images and Reports (2021) — 135 citations
• End-to-end privacy preserving deep learning on multi-institutional medical imaging (2021) — 478 citations
• Automatic Liver and Tumor Segmentation of CT and MRI Volumes using Cascaded Fully Convolutional Neural Networks (2017) — 365 citations