Renaud Gaujoux

Molecular Biology · 2010–2016

A researcher in the Science corpus: 2 papers; trusts 18 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

Whom Renaud Gaujoux trusts overall

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

  1. Patrik O. Hoyer
  2. Karthik Devarajan
  3. Daniel D. Lee
  4. Hyunsoo Kim
  5. Christos Boutsidis
  6. S. Li
  7. Pablo Tamayo
  8. Jean-Philippe Brunet
  9. Stefano Monti
  10. Michael W. Berry

Who trusts Renaud Gaujoux overall

  1. Zuguang Gu
  2. Francis Blokzijl
  3. D. Huebschmann
  4. Roel Janssen
  5. R. van Boxtel

Papers from Renaud Gaujoux's perspective

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

  1. Learning the parts of objects by non-negative matrix factorization
  2. Non-negative Matrix Factorization with Sparseness Constraints (Journal of machine learning research)
  3. Algorithms for Non-negative Matrix Factorization
  4. Consensus Clustering: A Resampling-Based Method for Class Discovery and Visualization of Gene Expression Microarray Data (Machine-mediated learning)
  5. Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values†
  6. Metagenes and molecular pattern discovery using matrix factorization (Proceedings of the National Academy of Sciences of the United States of America)
  7. Learning spatially localized, parts-based representation (Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001)
  8. Improving molecular cancer class discovery through sparse non-negative matrix factorization (Bioinform.)
  9. Non-negative sparse coding
  10. Visualizing Data using t-SNE

Their papers