Kristy Choi

Artificial Intelligence · with Ermon · 2019

A researcher in the Science corpus: 2 papers; trusts 167 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 60 citations into it; #26,759 of 35,345 by trust here, #21,316 by citations
• Computer Vision and Pattern Recognition — 47 citations into it; #16,392 of 21,575 by trust here, #14,151 by citations
• Generative Models — 36 citations into it; #1,538 of 1,956 by trust here, #1,601 by citations
• Probabilistic & Bayesian Methods — 21 citations into it
• Safety, Robustness & Interpretability — 16 citations into it
• Representation & Self-Supervised Learning — 13 citations into it
• Signal Processing — 10 citations into it
• Evaluation & Benchmarks — 8 citations into it

Whom Kristy Choi trusts overall

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

1. Yann LeCun
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Yoshua Bengio
5. Michael I. Jordan
6. Alex Krizhevsky
7. Kaiming He
8. Radford M. Neal
9. Karen Simonyan
10. Ilya Sutskever

Who trusts Kristy Choi overall

1. Luisa M. Zintgraf
2. Yuji Roh
3. Steven Euijong Whang
4. Vikram V. Ramaswamy
5. Melissa Hall

Papers from Kristy Choi's perspective

Ordered by how strongly the researchers Kristy Choi 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. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Fair Generative Modeling via Weak Supervision (2019) — 171 citations
• Meta-Amortized Variational Inference and Learning (2019) — 40 citations