Josh Beal
Artificial Intelligence · 2018–2020
A researcher in the Science corpus: 2 papers; trusts 36 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 65 citations into it
- Computer Vision and Pattern Recognition — 39 citations into it
- Model Architectures — 18 citations into it
- Privacy & Security — 15 citations into it
- Computational Theory and Mathematics — 7 citations into it
Whom Josh Beal trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Yoshua Bengio
- Ross B. Girshick
- Geoffrey E. Hinton
- Alex Krizhevsky
- Yann LeCun
- Shaoqing Ren
- Ilya Sutskever
- Diederik P. Kingma
- Tsung-Yi Lin
Who trusts Josh Beal overall
- Kai Han
- Fuyan Ma
- Xuran Pan
- Benjamin Graham
- Zhiliang Peng
- Hongwei Xue
- Yuxin Fang
- M. Sadegh Riazi
- Ronghang Hu
- Bin Sun
Papers from Josh Beal's perspective
Ordered by how strongly the researchers Josh Beal trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Toward Transformer-Based Object Detection (2020) — 257 citations
- Faster CryptoNets: Leveraging Sparsity for Real-World Encrypted Inference (2018) — 228 citations