Joseph D. Janizek

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 5 papers; trusts 124 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 102 citations into it; #29,140 of 35,345 by trust here, #19,873 by citations
• Computer Vision and Pattern Recognition — 63 citations into it
• Safety, Robustness & Interpretability — 36 citations into it
• Molecular Biology — 32 citations into it
• Radiology, Nuclear Medicine and Imaging — 27 citations into it
• Evaluation & Benchmarks — 17 citations into it
• Genetics — 17 citations into it
• Model Architectures — 10 citations into it

Whom Joseph D. Janizek trusts overall

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

1. Scott M. Lundberg
2. Geoffrey E. Hinton
3. Robert Tibshirani
4. Alex Krizhevsky
5. Yann LeCun
6. Karen Simonyan
7. Christian Szegedy
8. Lotfi A. Zadeh
9. Diederik P. Kingma
10. Yoshua Bengio

Who trusts Joseph D. Janizek overall

1. Alex J. DeGrave
2. Su-In Lee
3. Pranav Rajpurkar

Papers from Joseph D. Janizek's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. ImageNet Large Scale Visual Recognition Challenge
7. ImageNet: A large-scale hierarchical image database
8. Long Short-Term Memory
9. Attention is All you Need (Neural Information Processing Systems)
10. Going deeper with convolutions

Their papers

• Improving performance of deep learning models with axiomatic attribution priors and expected gradients (2020) — 355 citations
• Learning Explainable Models Using Attribution Priors (2019) — 85 citations
• Accurate classification of BRCA1 variants with saturation genome editing (2018) — 756 citations
• An adversarial approach for the robust classification of pneumonia from chest radiographs (2020) — 33 citations
• AI for radiographic COVID-19 detection selects shortcuts over signal (2020) — 727 citations