Karl Schultz

Probabilistic & Bayesian Methods · 2009

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Probabilistic & Bayesian Methods — 5 citations into it; #925 of 1,525 by trust here, #921 by citations

Whom Karl Schultz trusts overall

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

1. Avi Pfeffer
2. B. Taskar
3. Hoifung Poon
4. Taisuke Sato
5. Stuart J. Russell
6. Noah D. Goodman
7. Pedro M. Domingos
8. Michael I. Jordan

Who trusts Karl Schultz overall

1. Sebastian Riedel
2. Jeffrey Dalton
3. Lingfeng Yang
4. Ashesh Jain
5. Asad Basheer Sayeed
6. Daniel W. Barowy
7. Yao-Hung Hubert Tsai
8. Raphael Hoffmann
9. Johannes Borgström

Papers from Karl Schultz's perspective

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

1. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. ImageNet: A large-scale hierarchical image database
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• FACTORIE: Probabilistic Programming via Imperatively Defined Factor Graphs (2009) — 244 citations