Derek Doran
Artificial Intelligence · 2017–2020
A researcher in the Science corpus: 6 papers; trusts 709 researchers and is trusted by 22 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 258 citations into it; #7,645 of 35,345 by trust here, #6,796 by citations
- Computer Vision and Pattern Recognition — 159 citations into it; #5,599 of 21,575 by trust here, #5,422 by citations
- Safety, Robustness & Interpretability — 119 citations into it; #1,175 of 2,251 by trust here, #1,312 by citations
- Natural Language Processing — 69 citations into it
- Multimodal Learning — 37 citations into it; #345 of 1,211 by trust here, #610 by citations
- Evaluation & Benchmarks — 26 citations into it
- Model Architectures — 26 citations into it
- Signal Processing — 21 citations into it
Whom Derek Doran trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Geoffrey E. Hinton
- Alex Krizhevsky
- Yoshua Bengio
- Diederik P. Kingma
- Ilya Sutskever
- Ross B. Girshick
- Yann LeCun
- Li Fei-Fei
- Karen Simonyan
Who trusts Derek Doran overall
- Nadia Burkart
- Giulia Vilone
- Ronghang Hu
- Andreas Holzinger
- Gabrielle Ras
- Adrien Bennetot
- Marco F. Huber
- Sarah Wiegreffe
- Bertie Vidgen
- Zhe Gan
Papers from Derek Doran's perspective
Ordered by how strongly the researchers Derek Doran 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Visual Entailment: A Novel Task for Fine-Grained Image Understanding (2019) — 367 citations
- Explainable Deep Learning: A Field Guide for the Uninitiated (2020) — 452 citations
- Visual Entailment Task for Visually-Grounded Language Learning (2018) — 60 citations
- dbscan: Fast Density-Based Clustering with R (2019) — 794 citations
- Explaining Trained Neural Networks with Semantic Web Technologies: First Steps (2017) — 69 citations
- What Does Explainable AI Really Mean? A New Conceptualization of Perspectives (2017) — 483 citations