Babak Naimi
Ecological Modeling · 2011–2019
A researcher in the Science corpus: 4 papers; trusts 35 researchers and is trusted by 15 researchers here, as inferred from the citation graph.
Subfields
- Ecological Modeling — 152 citations into it; #452 of 2,530 by trust here, #1,154 by citations
- Nature and Landscape Conservation — 128 citations into it
- Ecology — 102 citations into it
- Ecology, Evolution, Behavior and Systematics — 24 citations into it
- Global and Planetary Change — 21 citations into it
- Genetics — 19 citations into it
- Artificial Intelligence — 17 citations into it; #12,698 of 35,345 by trust here, #23,077 by citations
- Statistics and Probability — 15 citations into it
Whom Babak Naimi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Jerome H. Friedman
- Miguel B. Araújo
- Jane Elith
- Eric R. Ziegel
- Michael P. Austin
- Trevor J. Hastie
- Catherine H. Graham
- Vladimir Naumovich Vapni
- Wilfried Thuiller
- C. Meynard
Who trusts Babak Naimi overall
- B. Blonder
- Adam B. Smith
- Canran Liu
- Emad Kaky
- Abraham Eustace
- Maria João Santos
- Damaris Zurell
- V. D. Cola
- G. Newell
- Victoria Nolan
Papers from Babak Naimi's perspective
Ordered by how strongly the researchers Babak Naimi trusts endorse each paper. Same corpus, a different order for every researcher.
- Generalized Linear Models
- Predicting species distribution: offering more than simple habitat models. (Ecology Letters)
- Predictive habitat distribution models in ecology
- New developments in museum-based informatics and applications in biodiversity analysis. (Trends in Ecology & Evolution)
- Greedy function approximation: A gradient boosting machine.
- BIOMOD – optimizing predictions of species distributions and projecting potential future shifts under global change
- Extinction risk from climate change (Nature)
- Spatial prediction of species distribution: an interface between ecological theory and statistical modelling
- A Coefficient of Agreement for Nominal Scales
- Extended statistical approaches to modelling spatial pattern in biodiversity in northeast New South Wales. II. Community-level modelling (Biodiversity and Conservation)
Their papers
- Standards for distribution models in biodiversity assessments (2019) — 988 citations
- sdm: a reproducible and extensible R platform for species distribution modelling (2016) — 1,023 citations
- Where is positional uncertainty a problem for species distribution modelling (2014) — 1,676 citations
- Spatial autocorrelation in predictors reduces the impact of positional uncertainty in occurrence data on species distribution modelling (2011) — 129 citations