Alexander J. Hartemink

Molecular Biology · 2000–2016

A researcher in the Science corpus: 7 papers; trusts 12 researchers and is trusted by 21 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 54 citations into it; #4,378 of 17,773 by trust here, #4,989 by citations
• Artificial Intelligence — 17 citations into it; #11,260 of 35,345 by trust here, #8,893 by citations
• Probabilistic & Bayesian Methods — 7 citations into it
• Computer Vision and Pattern Recognition — 6 citations into it; #9,583 of 21,575 by trust here, #9,079 by citations
• Statistical Learning Theory — 6 citations into it

Whom Alexander J. Hartemink trusts overall

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

1. Matthias W. Seeger
2. Radford M. Neal
3. Tom Minka
4. David A. McAllester
5. Dustin Boswell
6. Mário A. T. Figueiredo
7. David E. Heckerman
8. David E. Goldberg
9. Dirk Husmeier
10. Michael E. Tipping

Who trusts Alexander J. Hartemink overall

1. Michael Hecker
2. Florian Markowetz
3. Ilya Shmulevich
4. Jennie L. Reed
5. Reinhard C. Laubenbacher
6. Adam A. Margolin
7. Donna K. Slonim
8. Jing Yu
9. Harri Lähdesmäki
10. Katia Basso

Papers from Alexander J. Hartemink's perspective

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

1. Bayesian learning for neural networks
2. Atomic Decomposition by Basis Pursuit
3. Emergence of simple-cell receptive field properties by learning a sparse code for natural images
4. Sparse Bayesian Learning and the Relevan e Ve tor Ma hine
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. A theory of the learnable
7. ImageNet classification with deep convolutional neural networks
8. A wavelet tour of signal processing
9. Gradient-based learning applied to document recognition
10. Rademacher and Gaussian Complexities: Risk Bounds and Structural Results

Their papers

• Sparse multinomial logistic regression: fast algorithms and generalization bounds (2005) — 957 citations
• ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia (2012) — 1,852 citations
• Combining Location and Expression Data for Principled Discovery of Genetic Regulatory Network Models (2001) — 321 citations
• Using Graphical Models and Genomic Expression Data to Statistically Validate Models of Genetic Regulatory Networks (2000) — 448 citations
• Advances to Bayesian network inference for generating causal networks from observational biological data (2004) — 739 citations
• Enabling Privacy Preserving GWAS in Heterogeneous Human Populations (2016) — 107 citations
• Computational and experimental identification of novel human imprinted genes. (2007) — 405 citations