R. D. Blanton

Artificial Intelligence · 2017–2019

A researcher in the Science corpus: 2 papers; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 21 citations into it
• Computer Vision and Pattern Recognition — 18 citations into it
• Efficiency & Compression — 16 citations into it
• Model Architectures — 5 citations into it

Whom R. D. Blanton trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Matthieu Courbariaux
2. Diederik P. Kingma
3. Yoshua Bengio

Papers from R. D. Blanton's perspective

Ordered by how strongly the researchers R. D. Blanton trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Learning Multiple Layers of Features from Tiny Images
7. Attention is All you Need (Neural Information Processing Systems)
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Deep Learning
10. Going deeper with convolutions

Their papers

• LightNN: Filling the Gap between Conventional Deep Neural Networks and Binarized Networks (2017) — 38 citations
• FLightNNs: Lightweight Quantized Deep Neural Networks for Fast and Accurate Inference (2019) — 26 citations