Lingfeng Yang

Probabilistic & Bayesian Methods · with Goodman · 2014

A researcher in the Science corpus: 1 paper; trusts 9 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Probabilistic & Bayesian Methods — 6 citations into it; #890 of 1,525 by trust here, #1,313 by citations
• Artificial Intelligence — 5 citations into it

Whom Lingfeng Yang trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Avi Pfeffer
2. Mark Harman
3. Andrew McCallum
4. David Wingate
5. John Aycock
6. Noah D. Goodman
7. Andreas Stuhlmüller
8. Karl Schultz
9. Chris Lattner

Who trusts Lingfeng Yang overall

1. David Tolpin
2. Yura N. Perov
3. Jan-Willem van de Meent
4. Marco F. Cusumano-Towner
5. Frank D. Wood
6. Brooks Paige
7. Feras A. Saad
8. Hongseok Yang

Papers from Lingfeng Yang's perspective

Ordered by how strongly the researchers Lingfeng Yang trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Church: a language for generative models
3. Attention is All you Need (Neural Information Processing Systems)
4. ImageNet classification with deep convolutional neural networks
5. Long Short-Term Memory
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. Gradient-based learning applied to document recognition
9. IBAL: A Probabilistic Rational Programming Language
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Generating Efficient MCMC Kernels from Probabilistic Programs (2014) — 31 citations