Dylan Slack
Artificial Intelligence · 2019–2020
A researcher in the Science corpus: 3 papers; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 33 citations into it
- Safety, Robustness & Interpretability — 28 citations into it
Whom Dylan Slack trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Marco Tulio Ribeiro
- Scott M. Lundberg
- Been Kim
- Cynthia Rudin
- Zachary Chase Lipton
- Sameer Singh
- Cynthia Dwork
- Geoffrey E. Hinton
- Jacob Devlin
- Finale Doshi-Velez
Who trusts Dylan Slack overall
- Cynthia Rudin
- Sarah Wiegreffe
- Guy Van den Broeck
- Michael Chromik
- Yaron Shaposhnik
- Ana Marasovic
- Charles Marx
- Matthew James Vowels
- Anton Lykov
Papers from Dylan Slack's perspective
Ordered by how strongly the researchers Dylan Slack trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods (2019) — 1,143 citations
- Differentially Private Language Models Benefit from Public Pre-training (2020) — 71 citations
- How can we fool LIME and SHAP? Adversarial Attacks on Post hoc Explanation Methods (2019) — 70 citations