Yang Feng
Artificial Intelligence · with Gu · 2009–2022
A researcher in the Science corpus: 17 papers; trusts 624 researchers and is trusted by 28 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 284 citations into it; #8,633 of 35,345 by trust here, #8,893 by citations
- Natural Language Processing — 201 citations into it
- Computer Vision and Pattern Recognition — 165 citations into it; #12,524 of 21,575 by trust here, #8,722 by citations
- Model Architectures — 60 citations into it
- Statistics and Probability — 59 citations into it; #2,428 of 12,932 by trust here, #3,255 by citations
- Optimization & Training — 30 citations into it
- Evaluation & Benchmarks — 27 citations into it
- Efficiency & Compression — 17 citations into it
Whom Yang Feng trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Rico Sennrich
- Yoshua Bengio
- Ilya Sutskever
- Alex Krizhevsky
- Ronald J. Williams
- Diederik P. Kingma
- Jianqing Fan
- Dzmitry Bahdanau
- Kyunghyun Cho
Who trusts Yang Feng overall
- Jianqing Fan
- Shuhao Gu
- Mohsen Pourahmadi
- Degui Li
- Chenze Shao
- Clifford Lam
- Anders Gorst-rasmussen
- Bruce A. Craig
- Qing Mai
- Po-Ling Loh
Papers from Yang Feng's perspective
Ordered by how strongly the researchers Yang Feng trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- Bridging the Gap between Training and Inference for Neural Machine Translation (2019) — 276 citations
- A Projection-based Conditional Dependence Measure with Applications to High-dimensional Undirected Graphical Models. (2015) — 34 citations
- Nonparametric Independence Screening in Sparse Ultra-High Dimensional Additive Models (2009) — 602 citations
- Greedy Search with Probabilistic N-gram Matching for Neural Machine Translation (2018) — 29 citations
- NETWORK EXPLORATION VIA THE ADAPTIVE LASSO AND SCAD PENALTIES (2009) — 434 citations
- Overcoming Catastrophic Forgetting beyond Continual Learning: Balanced Training for Neural Machine Translation (2022) — 44 citations
- VARIABLE SELECTION AND PREDICTION WITH INCOMPLETE HIGH-DIMENSIONAL DATA (2016) — 52 citations
- Conversations Are Not Flat: Modeling the Dynamic Information Flow across Dialogue Utterances (2021) — 67 citations
- Importance-based Neuron Allocation for Multilingual Neural Machine Translation (2021) — 42 citations
- Pruning-then-Expanding Model for Domain Adaptation of Neural Machine Translation (2021) — 33 citations
- Token-level Adaptive Training for Neural Machine Translation (2020) — 39 citations
- Investigating Catastrophic Forgetting During Continual Training for Neural Machine Translation (2020) — 29 citations
- Future-Guided Incremental Transformer for Simultaneous Translation (2020) — 44 citations
- Improving Domain Adaptation Translation with Domain Invariant and Specific Information (2019) — 41 citations
- Modeling Fluency and Faithfulness for Diverse Neural Machine Translation (2019) — 28 citations
- Improving the Robustness of Speech Translation (2018) — 18 citations
- IMILAST: A Community Effort to Intercompare Extratropical Cyclone Detection and Tracking Algorithms (2013) — 527 citations