Sebastian Pölsterl

Journal of machine learning research · 2011–2020

A researcher in the Science corpus: 3 papers; trusts 0 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Whom Sebastian Pölsterl trusts overall

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

  1. Håvard Kvamme
  2. Hemant Ishwaran
  3. Torsten Hothorn
  4. Hajime Uno

Who trusts Sebastian Pölsterl overall

  1. J. Kenneth Tay
  2. Balasubramanian Narasimhan
  3. Trevor J. Hastie

Papers from Sebastian Pölsterl's perspective

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

  1. Random survival forests
  2. Scikit-learn: Machine Learning in Python
  3. Catastrophic forgetting in connectionist networks.
  4. Communication-Efficient Learning of Deep Networks from Decentralized Data
  5. Survival ensembles. (Biostatistics)
  6. Practical Secure Aggregation for Privacy-Preserving Machine Learning
  7. Multi-Institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentation
  8. Federated Learning: Strategies for Improving Communication Efficiency
  9. Prognostic/Clinical Prediction Models: Multivariable Prognostic Models: Issues in Developing Models, Evaluating Assumptions and Adequacy, and Measuring and Reducing Errors
  10. On the C-statistics for Evaluating Overall Adequacy of Risk Prediction Procedures with Censored Survival Data (Statistics in Medicine)

Their papers