D. Rückert

Privacy & Security · 2020

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Privacy & Security — 12 citations into it

Whom D. Rückert trusts overall

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

1. Joan Daemen
2. Arun Rajkumar

Who trusts D. Rückert overall

1. Qinbin Li

Papers from D. Rückert's perspective

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

1. Explaining and Harnessing Adversarial Examples
2. Membership Inference Attacks Against Machine Learning Models
3. The Algorithmic Foundations of Differential Privacy
4. Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures
5. CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy
6. ImageNet classification with deep convolutional neural networks
7. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
8. Scalable Private Learning with PATE
9. Gradient-based learning applied to document recognition
10. The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks

Their papers

• Secure, privacy-preserving and federated machine learning in medical imaging (2020) — 1,361 citations