Jonathan A. Tepper

Artificial Intelligence · 2018

A researcher in the Science corpus: 2 papers; trusts 32 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 24 citations into it; #11,016 of 35,345 by trust here, #15,542 by citations
• Natural Language Processing — 20 citations into it; #2,549 of 5,688 by trust here, #3,369 by citations
• Information Systems — 12 citations into it
• Safety, Robustness & Interpretability — 10 citations into it
• Communication — 6 citations into it; #803 of 3,460 by trust here, #1,198 by citations
• AI Ethics, Fairness & Society — 5 citations into it

Whom Jonathan A. Tepper trusts overall

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

1. Zeerak Talat
2. P. Burnap
3. Ji Ho Park
4. Thomas Davidson
5. Diederik P. Kingma
6. Anna Schmidt
7. Yashar Mehdad
8. Björn Gambäck
9. William Warner
10. Dirk Hovy

Who trusts Jonathan A. Tepper overall

1. Betty van Aken
2. Mladen Karan
3. Frederick Liu

Papers from Jonathan A. Tepper's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Attention is All you Need (Neural Information Processing Systems)
3. Hate Speech Detection with Comment Embeddings (The Web Conference)
4. Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
5. Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on Twitter
6. Detecting Hate Speech on the World Wide Web
7. ImageNet classification with deep convolutional neural networks
8. Long Short-Term Memory
9. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
10. Cyber Hate Speech on Twitter: An Application of Machine Classification and Statistical Modeling for Policy and Decision Making

Their papers

• Detecting Hate Speech on Twitter Using a Convolution-GRU Based Deep Neural Network (2018) — 653 citations
• Hate Speech Detection on Twitter: Feature Engineering v.s. Feature Selection (2018) — 31 citations