Ding Zhao
Artificial Intelligence · 2016–2020
A researcher in the Science corpus: 5 papers; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 76 citations into it
- Computer Vision and Pattern Recognition — 11 citations into it
- Probabilistic & Bayesian Methods — 10 citations into it
- Reinforcement Learning — 10 citations into it
- Statistics and Probability — 6 citations into it
- Management Science and Operations Research — 5 citations into it
- Optimization & Training — 5 citations into it
Whom Ding Zhao trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Reuven Y. Rubinstein
- Søren Asmussen
- Paul Glasserman
- Radford M. Neal
- Alex Graves
- Michael I. Jordan
- Geoffrey E. Hinton
- Jingyi Li
- Yoshua Bengio
- Diederik P. Kingma
Who trusts Ding Zhao overall
Papers from Ding Zhao's perspective
Ordered by how strongly the researchers Ding Zhao trusts endorse each paper. Same corpus, a different order for every researcher.
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- 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)
- Gradient-based learning applied to document recognition
- Layer Normalization
- Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Streaming End-to-end Speech Recognition for Mobile Devices (2018) — 676 citations
- A Streaming On-Device End-To-End Model Surpassing Server-Side Conventional Model Quality and Latency (2020) — 228 citations
- Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes (2020) — 38 citations
- A Tempt to Unify Heterogeneous Driving Databases using Traffic Primitives (2018) — 6 citations
- Accelerated Evaluation of Automated Vehicles Safety in Lane-Change Scenarios Based on Importance Sampling Techniques (2016) — 404 citations