Trang Pham
Artificial Intelligence · 2016–2017
A researcher in the Science corpus: 5 papers; trusts 40 researchers and is trusted by 12 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 56 citations into it; #11,338 of 35,345 by trust here, #9,465 by citations
- Model Architectures — 25 citations into it
- Computer Vision and Pattern Recognition — 18 citations into it
- Natural Language Processing — 16 citations into it
- Optimization & Training — 10 citations into it
- Representation & Self-Supervised Learning — 8 citations into it
- Probabilistic & Bayesian Methods — 7 citations into it
Whom Trang Pham trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- J. Urgen Schmidhuber
- Alex Graves
- Yoshua Bengio
- Sepp Hochreiter
- Diederik P. Kingma
- Alex Krizhevsky
- Ilya Sutskever
- Tomas Mikolov
- Yann LeCun
Who trusts Trang Pham overall
- Aleksandar Bojchevski
- Stephan Günnemann
- Yuan Luo
- Daniel Zügner
- Johannes Klicpera
- Katsuhiko Ishiguro
- William L. Hamilton
- Bidisha Samanta
- Benjamin Shickel
- Evan Zheran Liu
Papers from Trang Pham's perspective
Ordered by how strongly the researchers Trang Pham 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
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Column Networks for Collective Classification (2016) — 152 citations
- A deep language model for software code (2016) — 112 citations
- Graph Classification via Deep Learning with Virtual Nodes (2017) — 57 citations
- Predicting healthcare trajectories from medical records: A deep learning approach (2017) — 393 citations
- DeepCare: A Deep Dynamic Memory Model for Predictive Medicine (2016) — 304 citations