Marta Z. Kwiatkowska

Artificial Intelligence · 2002–2018

A researcher in the Science corpus: 12 papers; trusts 100 researchers and is trusted by 56 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 100 citations into it; #4,922 of 35,345 by trust here, #6,103 by citations
• Safety, Robustness & Interpretability — 79 citations into it; #532 of 2,251 by trust here, #684 by citations
• Computer Vision and Pattern Recognition — 49 citations into it; #6,491 of 21,575 by trust here, #10,334 by citations
• Computational Theory and Mathematics — 30 citations into it; #2,586 of 12,182 by trust here, #3,796 by citations
• Software — 22 citations into it; #273 of 1,227 by trust here, #383 by citations
• Program Analysis & Verification — 16 citations into it; #80 of 301 by trust here, #17 by citations
• Computer Networks and Communications — 15 citations into it; #8,035 of 9,886 by trust here, #7,832 by citations
• Signal Processing — 14 citations into it

Whom Marta Z. Kwiatkowska trusts overall

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

1. Ian J. Goodfellow
2. Xiaowei Huang
3. Christian Szegedy
4. Nicolas Papernot
5. Gethin Norman
6. Thomas Hérault
7. Geoffrey E. Hinton
8. Alex Krizhevsky
9. Guy Katz
10. Yann LeCun

Who trusts Marta Z. Kwiatkowska overall

1. Sohag Kabir
2. Jane Hillston
3. Gethin Norman
4. Wenjie Ruan
5. Vojtěch Forejt
6. Xiaowei Huang
7. David Parker
8. Emmanuel Letier
9. Christel Baier
10. Patrick Lincoln

Papers from Marta Z. Kwiatkowska's perspective

Ordered by how strongly the researchers Marta Z. Kwiatkowska 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Safety Verification of Deep Neural Networks (2016) — 1,011 citations
• Feature-Guided Black-Box Safety Testing of Deep Neural Networks (2017) — 247 citations
• PRISM: Probabilistic Symbolic Model Checker (2002) — 814 citations
• PRISM 4.0: Verification of Probabilistic Real-Time Systems (2011) — 2,723 citations
• Probabilistic symbolic model checking with PRISM: a hybrid approach (2004) — 527 citations
• Reachability Analysis of Deep Neural Networks with Provable Guarantees (2018) — 287 citations
• PRISM: A Tool for Automatic Verification of Probabilistic Systems (2006) — 779 citations
• Stochastic Model Checking (2007) — 657 citations
• Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for L0 Norm (2018) — 38 citations
• Concolic Testing for Deep Neural Networks (2018) — 351 citations
• Automated Verification Techniques for Probabilistic Systems (2011) — 382 citations
• Dynamic QoS Management and Optimization in Service-Based Systems (2011) — 410 citations