Daniel Kienitz
Artificial Intelligence · 2021
A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 18 citations into it
- Safety, Robustness & Interpretability — 10 citations into it
Whom Daniel Kienitz trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from Daniel Kienitz's perspective
Ordered by how strongly the researchers Daniel Kienitz trusts endorse each paper. Same corpus, a different order for every researcher.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Intriguing properties of neural networks
- Explaining and Harnessing Adversarial Examples
- Towards Deep Learning Models Resistant to Adversarial Attacks
- Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
- Towards Deep Neural Network Architectures Robust to Adversarial Examples
- Safety Verification of Deep Neural Networks
- AI2: Safety and Robustness Certification of Neural Networks with Abstract Interpretation
- Lipschitz Properties for Deep Convolutional Networks
- Robustness May Be at Odds with Accuracy
Their papers
- Property-driven Training: All You (N)Ever Wanted to Know About (2021) — 3 citations