Joshua Patterson
Artificial Intelligence · 2017–2020
A researcher in the Science corpus: 3 papers; trusts 159 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 111 citations into it
- Computer Vision and Pattern Recognition — 60 citations into it
- Safety, Robustness & Interpretability — 43 citations into it
- Optimization & Training — 21 citations into it
- Model Architectures — 19 citations into it
- ML Systems & Hardware — 14 citations into it
- Evaluation & Benchmarks — 11 citations into it
- Natural Language Processing — 10 citations into it
Whom Joshua Patterson trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Alex Krizhevsky
- Yann LeCun
- Kaiming He
- Leo Breiman
- Ilya Sutskever
- Ian J. Goodfellow
- Jerome H. Friedman
Who trusts Joshua Patterson overall
- Raghavendra Chalapathy
- Xiaoying Zhuang
- Sima Siami‐Namini
- Onur Avcı
- Hongwei Guo
- Sanjay Chawla
- Osama Abdeljaber
- Akbar Siami Namin
- Timon Rabczuk
- Victor-Emil Neagoe
Papers from Joshua Patterson's perspective
Ordered by how strongly the researchers Joshua Patterson 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)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge