Tianhao Zhang
Reinforcement Learning · with Abbeel · 2015–2018
A researcher in the Science corpus: 5 papers; trusts 126 researchers and is trusted by 171 researchers here, as inferred from the citation graph.
Subfields
- Reinforcement Learning — 98 citations into it; #627 of 2,242 by trust here, #420 by citations
- Artificial Intelligence — 94 citations into it; #3,807 of 35,345 by trust here, #3,138 by citations
- Control and Systems Engineering — 74 citations into it; #2,511 of 8,257 by trust here, #515 by citations
- Computer Vision and Pattern Recognition — 59 citations into it; #2,934 of 21,575 by trust here, #4,048 by citations
- Robotics & Control — 36 citations into it; #163 of 609 by trust here, #118 by citations
- Aerospace Engineering — 21 citations into it
- Biomedical Engineering — 17 citations into it
- Optimization & Training — 15 citations into it
Whom Tianhao Zhang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Sergey Levine
- Diederik P. Kingma
- Pieter Abbeel
- Stefan Schaal
- Jan Peters
- Geoffrey E. Hinton
- E. Todorov
- Jimmy Ba
- Chelsea Finn
- Alex Krizhevsky
Who trusts Tianhao Zhang overall
- Sergey Levine
- Chelsea Finn
- Ajay Mandlekar
- Lei Tai
- Corey Lynch
- Pieter Abbeel
- Peter R. Florence
- Jonathan Booher
- Tianhe Yu
- Han-Jia Ye
Papers from Tianhao Zhang's perspective
Ordered by how strongly the researchers Tianhao Zhang 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)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- One-Shot Visual Imitation Learning via Meta-Learning (2017) — 620 citations
- One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning (2018) — 385 citations
- Deep Imitation Learning for Complex Manipulation Tasks from Virtual Reality Teleoperation (2017) — 778 citations
- PLATO: Policy learning using adaptive trajectory optimization (2016) — 140 citations
- Learning deep control policies for autonomous aerial vehicles with MPC-guided policy search (2015) — 447 citations