Li Li

Artificial Intelligence · with Juefei-Xu · 2018

A researcher in the Science corpus: 2 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 48 citations into it
• Safety, Robustness & Interpretability — 36 citations into it

Whom Li Li trusts

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

1. David A. Wagner (in Artificial Intelligence)
2. Nicholas Carlini (in Artificial Intelligence)

Papers from Li Li's perspective

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

1. Gradient-based learning applied to document recognition
2. Learning Multiple Layers of Features from Tiny Images
3. ImageNet Large Scale Visual Recognition Challenge
4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. Rectified Linear Units Improve Restricted Boltzmann Machines
6. Explaining and Harnessing Adversarial Examples
7. GradientBased Learning Applied to Document Recognition
8. The mnist database of handwritten digits
9. Mastering the game of Go with deep neural networks and tree search
10. Large-Scale Video Classification with Convolutional Neural Networks

Their papers

• DeepMutation: Mutation Testing of Deep Learning Systems (2018) — 401 citations
• DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems (2018) — 708 citations