Philip Branch
Artificial Intelligence · 2007–2020
A researcher in the Science corpus: 2 papers; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 46 citations into it
- Signal Processing — 22 citations into it
- Computer Vision and Pattern Recognition — 19 citations into it
- Computer Networks and Communications — 17 citations into it
- Information Systems — 9 citations into it
- Statistics and Probability — 8 citations into it
Whom Philip Branch trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from Philip Branch's perspective
Ordered by how strongly the researchers Philip Branch 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)
- Gradient-based learning applied to document recognition
- Visualizing Data using t-SNE
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet: A large-scale hierarchical image database
Their papers
- A comprehensive survey of anomaly detection techniques for high dimensional big data (2020) — 408 citations
- A survey of covert channels and countermeasures in computer network protocols (2007) — 588 citations