Nikolaus Heinrich
2007–2010
A researcher in the Science corpus: 3 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.
Whom Nikolaus Heinrich trusts
Their strongest outbound trust, strongest first, inferred from their citations.
- David Ruppert (in Evaluation & Benchmarks)
Papers from Nikolaus Heinrich's perspective
Ordered by how strongly the researchers Nikolaus Heinrich trusts endorse each paper. Same corpus, a different order for every researcher.
- Learning with Kernels: support vector machines, regularization, optimization, and beyond
- The Elements of Statistical Learning: Data Mining, Inference, and Prediction
- Introduction to Support Vector Machines
- Current Status of Methods for Defining the Applicability Domain of (Quantitative) Structure-Activity Relationships (Alternatives to laboratory animals : ATLA)
- Can we estimate the accuracy of ADME-Tox predictions?
- An introduction to kernel-based learning algorithms
- Statistical Learning Theory
- This PDF file includes: Materials and Methods
- Neural Networks for Pattern Recognition
- GENERATIVE ADVERSARIAL NETS
Their papers
- Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules (2007) — 59 citations
- Benchmark Data Set for in Silico Prediction of Ames Mutagenicity (2009) — 352 citations
- A Maximum Common Subgraph Kernel Method for Predicting the Chromosome Aberration Test (2010) — 24 citations