Philip Adler

Artificial Intelligence · 2016

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

Subfields

• Artificial Intelligence — 30 citations into it; #23,980 of 35,345 by trust here, #9,641 by citations

Whom Philip Adler trusts overall

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

1. Trevor J. Hastie
2. J. Ross Quinlan
3. Robert Tibshirani
4. David Freedman
5. Jiaming Zeng
6. Yossi Rubner
7. Berk Ustun
8. Michael Feldman
9. Girish Chandrashekar
10. Cristian Bucila

Who trusts Philip Adler overall

1. Lu Zhang
2. Yongkai Wu
3. Xintao Wu
4. Thibault Laugel
5. Sarah Tan
6. Luca Oneto
7. Jaspreet Singh
8. Giulia Vilone
9. Dena F. Mujtaba
10. Brent Daniel Mittelstadt

Papers from Philip Adler's perspective

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

Their papers

• Auditing black-box models for indirect influence (2016) — 310 citations
• Machine-learning-assisted materials discovery using failed experiments (2016) — 1,511 citations
• Auditing Black-box Models by Obscuring Features (2016) — 26 citations