Jun-Ting Hsieh
Computer Vision and Pattern Recognition · 2017–2018
A researcher in the Science corpus: 2 papers; trusts 335 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 85 citations into it
- Artificial Intelligence — 61 citations into it
- Generative Models — 18 citations into it
- Representation & Self-Supervised Learning — 13 citations into it
- Optimization & Training — 5 citations into it
Whom Jun-Ting Hsieh trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Ilya Sutskever
- Alex Krizhevsky
- Karen Simonyan
- Kaiming He
- Yann LeCun
- Alex Graves
- J. Urgen Schmidhuber
Who trusts Jun-Ting Hsieh overall
- Vincent Le Guen
- Francesco Locatello
- Aidan Clark
- Guansong Pang
- Nicolas Thomé
- Jindong Jiang
- Michael Tschannen
- Jeff Donahue
- Chunhua Shen
- Ang Li
Papers from Jun-Ting Hsieh's perspective
Ordered by how strongly the researchers Jun-Ting Hsieh 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
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Learning to Decompose and Disentangle Representations for Video Prediction (2018) — 322 citations
- Graph Distillation for Action Detection with Privileged Modalities (2017) — 118 citations