Piotr (Peter) Mardziel

Artificial Intelligence · 2016–2020

A researcher in the Science corpus: 5 papers; trusts 76 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 80 citations into it; #15,680 of 35,345 by trust here, #9,170 by citations
• Safety, Robustness & Interpretability — 40 citations into it; #1,115 of 2,251 by trust here, #939 by citations
• Computer Vision and Pattern Recognition — 37 citations into it
• Natural Language Processing — 34 citations into it; #2,979 of 5,688 by trust here, #2,307 by citations
• Model Architectures — 15 citations into it
• Biophysics — 6 citations into it

Whom Piotr (Peter) Mardziel trusts overall

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

1. Karen Simonyan
2. Geoffrey E. Hinton
3. Ilya Sutskever
4. Sepp Hochreiter
5. Yoshua Bengio
6. Kevin Clark
7. Alex Graves
8. Alex Krizhevsky
9. Oriol Vinyals
10. Diederik P. Kingma

Who trusts Piotr (Peter) Mardziel overall

1. Emily Sheng
2. Jesse Vig
3. Kai-Wei Chang
4. Yusu Qian
5. Sunipa Dev
6. Divyansh Kaushik
7. Danielle Saunders
8. Angelina Wang
9. Zexue He
10. Premkumar Natarajan

Papers from Piotr (Peter) Mardziel's perspective

Ordered by how strongly the researchers Piotr (Peter) Mardziel trusts endorse each paper. Same corpus, a different order for every researcher.

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

Their papers

• Gender Bias in Neural Natural Language Processing (2018) — 408 citations
• Build It, Break It, Fix It: Contesting Secure Development (2016) — 78 citations
• Influence Paths for Characterizing Subject-Verb Number Agreement in LSTM Language Models (2020) — 10 citations
• Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks (2019) — 1,511 citations
• Proxy Non-Discrimination in Data-Driven Systems (2017) — 59 citations