Madlene Nussbaum

Environmental Engineering · 2018

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Environmental Engineering — 17 citations into it
• Artificial Intelligence — 11 citations into it
• Economics and Econometrics — 8 citations into it
• Global and Planetary Change — 7 citations into it
• Ecology — 5 citations into it

Whom Madlene Nussbaum trusts overall

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

1. Tomislav Hengl
2. Benedikt Gräler
3. Edzer J. Pebesma
4. Nicolai Meinshausen
5. Noel Cressie
6. U. Groemping
7. J. Etten
8. Trevor J. Hastie
9. Andy Liaw
10. Budiman Minasny

Papers from Madlene Nussbaum's perspective

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

1. Random Forests
2. Quantile Regression Forests
3. On spatial prediction of soil properties in the presence of a spatial trend: the empirical best linear unbiased predictor (E‐BLUP) with REML
4. Building Machines that Learn and Think Like People
5. Geostatistics For Environmental Scientists
6. Newer Classification and Regression Tree Techniques: Bagging and Random Forests for Ecological Prediction (Ecosystems)
7. Confidence Intervals for Random Forests: The Jackknife and the Infinitesimal Jackknife
8. Methods to interpolate soil categorical variables from profile observations: Lessons from Iran
9. Quantifying Uncertainty in Random Forests via Confidence Intervals and Hypothesis Tests
10. Do We Need More Training Data or Better Models for Object Detection?

Their papers

• Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variables (2018) — 919 citations