Jiajun Lu
Safety, Robustness & Interpretability · 2017
A researcher in the Science corpus: 4 papers; trusts 200 researchers and is trusted by 14 researchers here, as inferred from the citation graph.
Subfields
- Safety, Robustness & Interpretability — 67 citations into it; #868 of 2,251 by trust here, #831 by citations
- Artificial Intelligence — 60 citations into it; #12,716 of 35,345 by trust here, #8,893 by citations
- Computer Vision and Pattern Recognition — 55 citations into it; #16,572 of 21,575 by trust here, #10,010 by citations
- Signal Processing — 14 citations into it
- Hardware and Architecture — 8 citations into it
Whom Jiajun Lu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ian J. Goodfellow
- Alex Krizhevsky
- Christian Szegedy
- Kaiming He
- Geoffrey E. Hinton
- Nicholas Carlini
- Yann LeCun
- Ilya Sutskever
- Yoshua Bengio
- Joseph Redmon
Who trusts Jiajun Lu overall
- Ivan Evtimov
- Kevin Eykholt
- A. Serban
- Eric Wong
- Shang-Tse Chen
- Saumya Jetley
- Xiaoyong Yuan
- Naveed Akhtar
- Alhussein Fawzi
- Matthew Wicker
Papers from Jiajun Lu's perspective
Ordered by how strongly the researchers Jiajun Lu 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)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- NO Need to Worry about Adversarial Examples in Object Detection in Autonomous Vehicles (2017) — 293 citations
- Standard detectors aren't (currently) fooled by physical adversarial stop signs (2017) — 60 citations
- SafetyNet: Detecting and Rejecting Adversarial Examples Robustly (2017) — 403 citations
- Adversarial Examples that Fool Detectors (2017) — 159 citations